activity
20182022
most citedMulti-Domain Multi-Task Rehearsal for Lifelong Learning

5 citations · 18 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV20225 cited

A Benchmark of Video-Based Clothes-Changing Person Re-Identification

Likai Wang, Xiangqun Zhang, Ruize Han +4

Person re-identification (Re-ID) is a classical computer vision task and has achieved great progress so far. Recently, long-term Re-ID with clothes-changing has attracted increasin…

cs.CV20222 cited

View-Invariant Skeleton-based Action Recognition via Global-Local Contrastive Learning

Cunling Bian, Wei Feng, Fanbo Meng +1

Skeleton-based human action recognition has been drawing more interest recently due to its low sensitivity to appearance changes and the accessibility of more skeleton data. Howeve…

cs.CV20225 cited

MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting

Xiaoguang Li, Qing Guo, Di Lin +3

Although achieving significant progress, existing deep generative inpainting methods are far from real-world applications due to the low generalization across different scenes. As…

cs.CV20221 cited

Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining

Qing Guo, Jingyang Sun, Felix Juefei-Xu +4

Deraining is a significant and fundamental computer vision task, aiming to remove the rain streaks and accumulations in an image or video captured under a rainy day. Existing derai…

cs.LG20205 cited

Multi-Domain Multi-Task Rehearsal for Lifelong Learning

Fan Lyu, Shuai Wang, Wei Feng +3

Rehearsal, seeking to remind the model by storing old knowledge in lifelong learning, is one of the most effective ways to mitigate catastrophic forgetting, i.e., biased forgetting…

cs.CV2020

MUTATT: Visual-Textual Mutual Guidance for Referring Expression Comprehension

Shuai Wang, Fan Lyu, Wei Feng +1

Referring expression comprehension (REC) aims to localize a text-related region in a given image by a referring expression in natural language. Existing methods focus on how to bui…