7 citations
5 papers
Learning Resolution-Invariant Deep Representations for Person Re-Identification
Yun-Chun Chen, Yu-Jhe Li, Xiaofei Du +1
Person re-identification (re-ID) solves the task of matching images across cameras and is among the research topics in vision community. Since query images in real-world scenarios…
Leveraging Motion Priors in Videos for Improving Human Segmentation
Yu-Ting Chen, Wen-Yen Chang, Hai-Lun Lu +2
Despite many advances in deep-learning based semantic segmentation, performance drop due to distribution mismatch is often encountered in the real world. Recently, a few domain ada…
Efficient Uncertainty Estimation for Semantic Segmentation in Videos
Po-Yu Huang, Wan-Ting Hsu, Chun-Yueh Chiu +2
Uncertainty estimation in deep learning becomes more important recently. A deep learning model can't be applied in real applications if we don't know whether the model is certain a…
Toward Scale-Invariance and Position-Sensitive Region Proposal Networks
Hsueh-Fu Lu, Xiaofei Du, Ping-Lin Chang
Accurately localising object proposals is an important precondition for high detection rate for the state-of-the-art object detection frameworks. The accuracy of an object detectio…
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
Yu-Jhe Li, Fu-En Yang, Yen-Cheng Liu +3
Person re-identification (Re-ID) aims at recognizing the same person from images taken across different cameras. To address this task, one typically requires a large amount labeled…