activity
20222025
most citedSLCGC: A lightweight Self-supervised Low-pass Contrastive Graph Clustering Network for Hyperspectral Images

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

collaborators

11 papers

cs.CV2023

Relit-NeuLF: Efficient Relighting and Novel View Synthesis via Neural 4D Light Field

Zhong Li, Liangchen Song, Zhang Chen +4

In this paper, we address the problem of simultaneous relighting and novel view synthesis of a complex scene from multi-view images with a limited number of light sources. We propo…

cs.CV2023

NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions

Zhang Chen, Zhong Li, Liangchen Song +4

We present a novel type of neural fields that uses general radial bases for signal representation. State-of-the-art neural fields typically rely on grid-based representations for s…

cs.CV2023

SOAR: Scene-debiasing Open-set Action Recognition

Yuanhao Zhai, Ziyi Liu, Zhenyu Wu +5

Deep learning models have a risk of utilizing spurious clues to make predictions, such as recognizing actions based on the background scene. This issue can severely degrade the ope…

cs.CV2023

Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning

Yuanhao Zhai, Tianyu Luan, David Doermann +1

As advanced image manipulation techniques emerge, detecting the manipulation becomes increasingly important. Despite the success of recent learning-based approaches for image manip…

cs.CV2023

Language-guided Human Motion Synthesis with Atomic Actions

Yuanhao Zhai, Mingzhen Huang, Tianyu Luan +5

Language-guided human motion synthesis has been a challenging task due to the inherent complexity and diversity of human behaviors. Previous methods face limitations in generalizat…

cs.CV2023

Source-Free Domain Adaptation for Medical Image Segmentation via Prototype-Anchored Feature Alignment and Contrastive Learning

Qinji Yu, Nan Xi, Junsong Yuan +3

Unsupervised domain adaptation (UDA) has increasingly gained interests for its capacity to transfer the knowledge learned from a labeled source domain to an unlabeled target domain…