|
Records |
Links |
|
Author |
Lichao Zhang; Martin Danelljan; Abel Gonzalez-Garcia; Joost Van de Weijer; Fahad Shahbaz Khan |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Multi-Modal Fusion for End-to-End RGB-T Tracking |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2252-2261 |
|
|
Keywords |
|
|
|
Abstract |
We propose an end-to-end tracking framework for fusing the RGB and TIR modalities in RGB-T tracking. Our baseline tracker is DiMP (Discriminative Model Prediction), which employs a carefully designed target prediction network trained end-to-end using a discriminative loss. We analyze the effectiveness of modality fusion in each of the main components in DiMP, i.e. feature extractor, target estimation network, and classifier. We consider several fusion mechanisms acting at different levels of the framework, including pixel-level, feature-level and response-level. Our tracker is trained in an end-to-end manner, enabling the components to learn how to fuse the information from both modalities. As data to train our model, we generate a large-scale RGB-T dataset by considering an annotated RGB tracking dataset (GOT-10k) and synthesizing paired TIR images using an image-to-image translation approach. We perform extensive experiments on VOT-RGBT2019 dataset and RGBT210 dataset, evaluating each type of modality fusing on each model component. The results show that the proposed fusion mechanisms improve the performance of the single modality counterparts. We obtain our best results when fusing at the feature-level on both the IoU-Net and the model predictor, obtaining an EAO score of 0.391 on VOT-RGBT2019 dataset. With this fusion mechanism we achieve the state-of-the-art performance on RGBT210 dataset. |
|
|
Address |
Seul; Corea; October 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCVW |
|
|
Notes |
LAMP; 600.109; 600.141; 600.120 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ZDG2019 |
Serial |
3279 |
|
Permanent link to this record |
|
|
|
|
Author |
Javad Zolfaghari Bengar; Abel Gonzalez-Garcia; Gabriel Villalonga; Bogdan Raducanu; Hamed H. Aghdam; Mikhail Mozerov; Antonio Lopez; Joost Van de Weijer |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Temporal Coherence for Active Learning in Videos |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
914-923 |
|
|
Keywords |
|
|
|
Abstract |
Autonomous driving systems require huge amounts of data to train. Manual annotation of this data is time-consuming and prohibitively expensive since it involves human resources. Therefore, active learning emerged as an alternative to ease this effort and to make data annotation more manageable. In this paper, we introduce a novel active learning approach for object detection in videos by exploiting temporal coherence. Our active learning criterion is based on the estimated number of errors in terms of false positives and false negatives. The detections obtained by the object detector are used to define the nodes of a graph and tracked forward and backward to temporally link the nodes. Minimizing an energy function defined on this graphical model provides estimates of both false positives and false negatives. Additionally, we introduce a synthetic video dataset, called SYNTHIA-AL, specially designed to evaluate active learning for video object detection in road scenes. Finally, we show that our approach outperforms active learning baselines tested on two datasets. |
|
|
Address |
Seul; Corea; October 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCVW |
|
|
Notes |
LAMP; ADAS; 600.124; 602.200; 600.118; 600.120; 600.141 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ZGV2019 |
Serial |
3294 |
|
Permanent link to this record |
|
|
|
|
Author |
Mohammed Al Rawi; Ernest Valveny |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Compact and Efficient Multitask Learning in Vision, Language and Speech |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2933-2942 |
|
|
Keywords |
|
|
|
Abstract |
Across-domain multitask learning is a challenging area of computer vision and machine learning due to the intra-similarities among class distributions. Addressing this problem to cope with the human cognition system by considering inter and intra-class categorization and recognition complicates the problem even further. We propose in this work an effective holistic and hierarchical learning by using a text embedding layer on top of a deep learning model. We also propose a novel sensory discriminator approach to resolve the collisions between different tasks and domains. We then train the model concurrently on textual sentiment analysis, speech recognition, image classification, action recognition from video, and handwriting word spotting of two different scripts (Arabic and English). The model we propose successfully learned different tasks across multiple domains. |
|
|
Address |
Seul; Korea; October 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCVW |
|
|
Notes |
DAG; 600.121; 600.129 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RaV2019 |
Serial |
3365 |
|
Permanent link to this record |
|
|
|
|
Author |
Alejandro Cartas; Jordi Luque; Petia Radeva; Carlos Segura; Mariella Dimiccoli |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Seeing and Hearing Egocentric Actions: How Much Can We Learn? |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
4470-4480 |
|
|
Keywords |
|
|
|
Abstract |
Our interaction with the world is an inherently multimodal experience. However, the understanding of human-to-object interactions has historically been addressed focusing on a single modality. In particular, a limited number of works have considered to integrate the visual and audio modalities for this purpose. In this work, we propose a multimodal approach for egocentric action recognition in a kitchen environment that relies on audio and visual information. Our model combines a sparse temporal sampling strategy with a late fusion of audio, spatial, and temporal streams. Experimental results on the EPIC-Kitchens dataset show that multimodal integration leads to better performance than unimodal approaches. In particular, we achieved a 5.18% improvement over the state of the art on verb classification. |
|
|
Address |
Seul; Korea; October 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCVW |
|
|
Notes |
MILAB; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ CLR2019b |
Serial |
3385 |
|
Permanent link to this record |
|
|
|
|
Author |
Armin Mehri; Angel Sappa |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Colorizing Near Infrared Images through a Cyclic Adversarial Approach of Unpaired Samples |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision and Pattern Recognition-Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
This paper presents a novel approach for colorizing near infrared (NIR) images. The approach is based on image-to-image translation using a Cycle-Consistent adversarial network for learning the color channels on unpaired dataset. This architecture is able to handle unpaired datasets. The approach uses as generators tailored networks that require less computation times, converge faster and generate high quality samples. The obtained results have been quantitatively—using standard evaluation metrics—and qualitatively evaluated showing considerable improvements with respect to the state of the art |
|
|
Address |
Long beach; California; USA; June 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPRW |
|
|
Notes |
MSIAU; 600.130; 601.349; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MeS2019 |
Serial |
3271 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Suarez; Angel Sappa; Boris X. Vintimilla; Riad I. Hammoud |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Image Vegetation Index through a Cycle Generative Adversarial Network |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision and Pattern Recognition-Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
This paper proposes a novel approach to estimate the Normalized Difference Vegetation Index (NDVI) just from an RGB image. The NDVI values are obtained by using images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The cycled GAN network is able to obtain a NIR image from a given gray scale image. It is trained by using unpaired set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are obtained from the provided RGB images). Then, the NIR image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous approaches are also provided. |
|
|
Address |
Long beach; California; USA; June 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPRW |
|
|
Notes |
MSIAU; 600.130; 601.349; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SSV2019 |
Serial |
3272 |
|
Permanent link to this record |
|
|
|
|
Author |
Ajian Liu; Jun Wan; Sergio Escalera; Hugo Jair Escalante; Zichang Tan; Qi Yuan; Kai Wang; Chi Lin; Guodong Guo; Isabelle Guyon; Stan Z. Li |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Multi-Modal Face Anti-Spoofing Attack Detection Challenge at CVPR2019 |
Type |
Conference Article |
|
Year |
2019 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision and Pattern Recognition-Workshop |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Anti-spoofing attack detection is critical to guarantee the security of face-based authentication and facial analysis systems. Recently, a multi-modal face anti-spoofing dataset, CASIA-SURF, has been released with the goal of boosting research in this important topic. CASIA-SURF is the largest public data set for facial anti-spoofing attack detection in terms of both, diversity and modalities: it comprises 1,000 subjects and 21,000 video samples. We organized a challenge around this novel resource to boost research in the subject. The Chalearn LAP multi-modal face anti-spoofing attack detection challenge attracted more than 300 teams for the development phase with a total of 13 teams qualifying for the final round. This paper presents an overview of the challenge, including its design, evaluation protocol and a summary of results. We analyze the top ranked solutions and draw conclusions derived from the competition. In addition we outline future work directions. |
|
|
Address |
California; June 2019 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPRW |
|
|
Notes |
HuPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ LWE2019 |
Serial |
3329 |
|
Permanent link to this record |
|
|
|
|
Author |
B. Moghaddam; David Guillamet; Jordi Vitria |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
, Local Appearance-Based Models using High-Order Statistics of Image Features |
Type |
Miscellaneous |
|
Year |
2003 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ MGV2003 |
Serial |
395 |
|
Permanent link to this record |
|
|
|
|
Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
Type |
Conference Article |
|
Year |
2011 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Computer Vision – Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
2042-2049 |
|
|
Keywords |
IEEE International Conference on Computer Vision – Workshops |
|
|
Abstract |
Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
IEEE |
Place of Publication |
Barcelona (Spain) |
Editor |
|
|
|
Language |
English |
Summary Language |
English |
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCVW |
|
|
Notes |
IAM; ADAS |
Approved |
no |
|
|
Call Number |
IAM @ iam @ MGH2011 |
Serial |
1682 |
|
Permanent link to this record |
|
|
|
|
Author |
Bogdan Raducanu; Jordi Vitria; D. Gatica-Perez |
![goto web page (via DOI) doi](img/doi.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
You are Fired! Nonverbal Role Analysis in Competitive Meetings |
Type |
Conference Article |
|
Year |
2009 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Audio, Speech and Signal Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1949–1952 |
|
|
Keywords |
|
|
|
Abstract |
This paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. For our study, we made use of ldquoThe Apprenticerdquo reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. The current study was carried out using nonverbal audio cues. Results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. |
|
|
Address |
Taipei, Taiwan |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1520-6149 |
ISBN |
978-1-4244-2353-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICASSP |
|
|
Notes |
OR;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ RVG2009 |
Serial |
1154 |
|
Permanent link to this record |
|
|
|
|
Author |
Danna Xue; Luis Herranz; Javier Vazquez; Yanning Zhang |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Burst Perception-Distortion Tradeoff: Analysis and Evaluation |
Type |
Conference Article |
|
Year |
2023 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Acoustics, Speech and Signal Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Burst image restoration attempts to effectively utilize the complementary cues appearing in sequential images to produce a high-quality image. Most current methods use all the available images to obtain the reconstructed image. However, using more images for burst restoration is not always the best option regarding reconstruction quality and efficiency, as the images acquired by handheld imaging devices suffer from degradation and misalignment caused by the camera noise and shake. In this paper, we extend the perception-distortion tradeoff theory by introducing multiple-frame information. We propose the area of the unattainable region as a new metric for perception-distortion tradeoff evaluation and comparison. Based on this metric, we analyse the performance of burst restoration from the perspective of the perception-distortion tradeoff under both aligned bursts and misaligned bursts situations. Our analysis reveals the importance of inter-frame alignment for burst restoration and shows that the optimal burst length for the restoration model depends both on the degree of degradation and misalignment. |
|
|
Address |
Rodhes Islands; Greece; June 2023 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICASSP |
|
|
Notes |
CIC; MACO |
Approved |
no |
|
|
Call Number |
Admin @ si @ XHV2023 |
Serial |
3909 |
|
Permanent link to this record |
|
|
|
|
Author |
Yifan Wang; Luka Murn; Luis Herranz; Fei Yang; Marta Mrak; Wei Zhang; Shuai Wan; Marc Gorriz Blanch |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Efficient Super-Resolution for Compression Of Gaming Videos |
Type |
Conference Article |
|
Year |
2023 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Acoustics, Speech and Signal Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Due to the increasing demand for game-streaming services, efficient compression of computer-generated video is more critical than ever, especially when the available bandwidth is low. This paper proposes a super-resolution framework that improves the coding efficiency of computer-generated gaming videos at low bitrates. Most state-of-the-art super-resolution networks generalize over a variety of RGB inputs and use a unified network architecture for frames of different levels of degradation, leading to high complexity and redundancy. Since games usually consist of a limited number of fixed scenarios, we specialize one model for each scenario and assign appropriate network capacities for different QPs to perform super-resolution under the guidance of reconstructed high-quality luma components. Experimental results show that our framework achieves a superior quality-complexity trade-off compared to the ESRnet baseline, saving at most 93.59% parameters while maintaining comparable performance. The compression efficiency compared to HEVC is also improved by more than 17% BD-rate gain. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICASSP |
|
|
Notes |
LAMP; MACO |
Approved |
no |
|
|
Call Number |
Admin @ si @ WMH2023 |
Serial |
3911 |
|
Permanent link to this record |
|
|
|
|
Author |
Mingyi Yang; Luis Herranz; Fei Yang; Luka Murn; Marc Gorriz Blanch; Shuai Wan; Fuzheng Yang; Marta Mrak |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Semantic Preprocessor for Image Compression for Machines |
Type |
Conference Article |
|
Year |
2023 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Acoustics, Speech and Signal Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Visual content is being increasingly transmitted and consumed by machines rather than humans to perform automated content analysis tasks. In this paper, we propose an image preprocessor that optimizes the input image for machine consumption prior to encoding by an off-the-shelf codec designed for human consumption. To achieve a better trade-off between the accuracy of the machine analysis task and bitrate, we propose leveraging pre-extracted semantic information to improve the preprocessor’s ability to accurately identify and filter out task-irrelevant information. Furthermore, we propose a two-part loss function to optimize the preprocessor, consisted of a rate-task performance loss and a semantic distillation loss, which helps the reconstructed image obtain more information that contributes to the accuracy of the task. Experiments show that the proposed preprocessor can save up to 48.83% bitrate compared with the method without the preprocessor, and save up to 36.24% bitrate compared to existing preprocessors for machine vision. |
|
|
Address |
Rodhes Islands; Greece; June 2023 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICASSP |
|
|
Notes |
MACO; LAMP |
Approved |
no |
|
|
Call Number |
Admin @ si @ YHY2023 |
Serial |
3912 |
|
Permanent link to this record |
|
|
|
|
Author |
Lei Kang; Lichao Zhang; Dazhi Jiang |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Learning Robust Self-Attention Features for Speech Emotion Recognition with Label-Adaptive Mixup |
Type |
Conference Article |
|
Year |
2023 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE International Conference on Acoustics, Speech and Signal Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Speech Emotion Recognition (SER) is to recognize human emotions in a natural verbal interaction scenario with machines, which is considered as a challenging problem due to the ambiguous human emotions. Despite the recent progress in SER, state-of-the-art models struggle to achieve a satisfactory performance. We propose a self-attention based method with combined use of label-adaptive mixup and center loss. By adapting label probabilities in mixup and fitting center loss to the mixup training scheme, our proposed method achieves a superior performance to the state-of-the-art methods. |
|
|
Address |
Rodhes Islands; Greece; June 2023 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICASSP |
|
|
Notes |
LAMP |
Approved |
no |
|
|
Call Number |
Admin @ si @ KZJ2023 |
Serial |
3984 |
|
Permanent link to this record |
|
|
|
|
Author |
Fadi Dornaika; Angel Sappa |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Real Time on Board Stereo Camera Pose through Image Registration |
Type |
Conference Article |
|
Year |
2008 |
Publication ![sorted by Publication field, descending order (down)](img/sort_desc.gif) |
IEEE Intelligent Vehicles Symposium, |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
804–809 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Eindhoven (Netherlands) |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ DoS2008a |
Serial |
1015 |
|
Permanent link to this record |