1 citations · 1 across the 3 of their papers we have counts for
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Combating Noisy Labels through Fostering Self- and Neighbor-Consistency
Zeren Sun, Yazhou Yao, Tongliang Liu +3
Label noise is pervasive in various real-world scenarios, posing challenges in supervised deep learning. Deep networks are vulnerable to such label-corrupted samples due to the mem…
OmniGaze: Reward-inspired Generalizable Gaze Estimation In The Wild
Hongyu Qu, Jianan Wei, Xiangbo Shu +3
Current 3D gaze estimation methods struggle to generalize across diverse data domains, primarily due to i) the scarcity of annotated datasets, and ii) the insufficient diversity of…
FTMoMamba: Motion Generation with Frequency and Text State Space Models
Chengjian Li, Xiangbo Shu, Qiongjie Cui +2
Diffusion models achieve impressive performance in human motion generation. However, current approaches typically ignore the significance of frequency-domain information in capturi…
Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object Segmentation
Gensheng Pei, Yazhou Yao, Jianbo Jiao +3
Conventional video object segmentation (VOS) methods usually necessitate a substantial volume of pixel-level annotated video data for fully supervised learning. In this paper, we p…