activity
20212023
most citedDarkVision: A Benchmark for Low-light Image/Video Perception

2 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV20231 cited

Consolidator: Mergeable Adapter with Grouped Connections for Visual Adaptation

Tianxiang Hao, Hui Chen, Yuchen Guo +1

Recently, transformers have shown strong ability as visual feature extractors, surpassing traditional convolution-based models in various scenarios. However, the success of vision…

cs.CL20231 cited

Hi Sheldon! Creating Deep Personalized Characters from TV Shows

Meidai Xuanyuan, Yuwang Wang, Honglei Guo +4

Imagine an interesting multimodal interactive scenario that you can see, hear, and chat with an AI-generated digital character, who is capable of behaving like Sheldon from The Big…

cs.CV20231 cited

Box-Level Active Detection

Mengyao Lyu, Jundong Zhou, Hui Chen +7

Active learning selects informative samples for annotation within budget, which has proven efficient recently on object detection. However, the widely used active detection benchma…

cs.CV2023

X-ReID: Cross-Instance Transformer for Identity-Level Person Re-Identification

Leqi Shen, Tao He, Yuchen Guo +1

Currently, most existing person re-identification methods use Instance-Level features, which are extracted only from a single image. However, these Instance-Level features can easi…

cs.CV20232 cited

DarkVision: A Benchmark for Low-light Image/Video Perception

Bo Zhang, Yuchen Guo, Runzhao Yang +4

Imaging and perception in photon-limited scenarios is necessary for various applications, e.g., night surveillance or photography, high-speed photography, and autonomous driving. I…

cs.CV20221 cited

Automatic Landmark Detection and Registration of Brain Cortical Surfaces via Quasi-Conformal Geometry and Convolutional Neural Networks

Yuchen Guo, Qiguang Chen, Gary P. T. Choi +1

In medical imaging, surface registration is extensively used for performing systematic comparisons between anatomical structures, with a prime example being the highly convoluted b…