Zobrazeno 1 - 10
of 568
pro vyhledávání: '"Kot Alex"'
Autor:
Yu, Yi, Wang, Yufei, Yang, Wenhan, Guo, Lanqing, Lu, Shijian, Duan, Ling-Yu, Tan, Yap-Peng, Kot, Alex C.
Recent advancements in deep learning-based compression techniques have surpassed traditional methods. However, deep neural networks remain vulnerable to backdoor attacks, where pre-defined triggers induce malicious behaviors. This paper introduces a
Externí odkaz:
http://arxiv.org/abs/2412.01646
Autor:
Han, Xiyu, Zhong, Xian, Huang, Wenxin, Jia, Xuemei, Liu, Wenxuan, Yu, Xiaohan, Kot, Alex Chichung
Cloth-changing person re-identification (CC-ReID) aims to match individuals across multiple surveillance cameras despite variations in clothing. Existing methods typically focus on mitigating the effects of clothing changes or enhancing ID-relevant f
Externí odkaz:
http://arxiv.org/abs/2412.01345
Given a natural language query, video moment retrieval aims to localize the described temporal moment in an untrimmed video. A major challenge of this task is its heavy dependence on labor-intensive annotations for training. Unlike existing works tha
Externí odkaz:
http://arxiv.org/abs/2412.00811
Autor:
Bao, Peijun, Kot, Alex C.
This paper presents SimBase, a simple yet effective baseline for temporal video grounding. While recent advances in temporal grounding have led to impressive performance, they have also driven network architectures toward greater complexity, with a r
Externí odkaz:
http://arxiv.org/abs/2411.07945
Existing prompt learning methods in Vision-Language Models (VLM) have effectively enhanced the transfer capability of VLM to downstream tasks, but they suffer from a significant decline in generalization due to severe overfitting. To address this iss
Externí odkaz:
http://arxiv.org/abs/2410.10247
Person Re-identification (Person ReID) has advanced significantly in fully supervised and domain generalized Person R e ID. However, methods developed for one task domain transfer poorly to the other. An ideal Person ReID method should be effective r
Externí odkaz:
http://arxiv.org/abs/2410.08466
Supervised Person Re-identification (Person ReID) methods have achieved excellent performance when training and testing within one camera network. However, they usually suffer from considerable performance degradation when applied to different camera
Externí odkaz:
http://arxiv.org/abs/2410.08456
Person Re-identification (Person ReID) has progressed to a level where single-domain supervised Person ReID performance has saturated. However, such methods experience a significant drop in performance when trained and tested across different dataset
Externí odkaz:
http://arxiv.org/abs/2410.08460
Visible and Infrared Image Fusion (VIF) has garnered significant interest across a wide range of high-level vision tasks, such as object detection and semantic segmentation. However, the evaluation of VIF methods remains challenging due to the absenc
Externí odkaz:
http://arxiv.org/abs/2410.06811
Face Anti-Spoofing (FAS) research is challenged by the cross-domain problem, where there is a domain gap between the training and testing data. While recent FAS works are mainly model-centric, focusing on developing domain generalization algorithms f
Externí odkaz:
http://arxiv.org/abs/2409.03501