5 citations · 8 across the 6 of their papers we have counts for
7 papers
StimFlow: Synthesizing Brain Activity from Images via Stimulus-conditioned Flow Matching
Bui Van Hung, Dang Thanh Vu, Hoang-Son Vo +3
The inherent variability of fMRI responses across trials encourages a generative view of the stimulus-to-response mapping. Prior generative encoders often operate in compressed lat…
Task-disentangled Low-Rank Adaptation for Versatile Audio-visual Multi-modal Learning Tasks within a Unified Framework
Hanyu Xuan, Mengqi Zhang, Junjun Mao +5
Inspired by human multi-modal perception, Audio-Visual Multi-Modal Learning (AVMML) integrates auditory and visual information to leverage complementary cross-modal cues, enabling…
Structure-Guided Mixed Masked Pretraining and Spatial Continuity Regularization for Printed Circuit Board Defect Detection
Peitong Wang, Nuo Wang, Enxin Qin +3
Printed circuit board (PCB) defect detection is an essential part of automated optical inspection (AOI); yet it remains challenging in practice because many defects are tiny, low-c…
GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection
Yanguang Sun, Hanyu Xuan, Jian Yang +1
Recently, biological perception has been a powerful tool for handling the camouflaged object detection (COD) task. However, most existing methods are heavily dependent on the local…
Frequency-Spatial Entanglement Learning for Camouflaged Object Detection
Yanguang Sun, Chunyan Xu, Jian Yang +2
Camouflaged object detection has attracted a lot of attention in computer vision. The main challenge lies in the high degree of similarity between camouflaged objects and their sur…
Semi-Supervised Video Inpainting with Cycle Consistency Constraints
Zhiliang Wu, Hanyu Xuan, Changchang Sun +2
Deep learning-based video inpainting has yielded promising results and gained increasing attention from researchers. Generally, these methods usually assume that the corrupted regi…
Robust Audio-Visual Instance Discrimination via Active Contrastive Set Mining
Hanyu Xuan, Yihong Xu, Shuo Chen +4
The recent success of audio-visual representation learning can be largely attributed to their pervasive property of audio-visual synchronization, which can be used as self-annotate…