1 citations · 1 across the 8 of their papers we have counts for
9 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…
BeatDance: Generating Beat-Consistent 3D Dance with Hierarchical Spatial-Temporal Modeling
Xiaojian Shen, Dahu Shi, Jianrong Zhang +7
Generating realistic 3D dance from music is a challenging task that requires accurate synchronization with musical rhythms while capturing the spatial complexity of human motion. A…
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…
Perception-oriented Bidirectional Attention Network for Image Super-resolution Quality Assessment
Yixiao Li, Xiaoyuan Yang, Guanghui Yue +6
Many super-resolution (SR) algorithms have been proposed to increase image resolution. However, full-reference (FR) image quality assessment (IQA) metrics for comparing and evaluat…
VQualA 2025 Challenge on Image Super-Resolution Generated Content Quality Assessment: Methods and Results
Yixiao Li, Xin Li, Chris Wei Zhou +28
This paper presents the ISRGC-Q Challenge, built upon the Image Super-Resolution Generated Content Quality Assessment (ISRGen-QA) dataset, and organized as part of the Visual Quali…
CLIP-DQA: Blindly Evaluating Dehazed Images from Global and Local Perspectives Using CLIP
Yirui Zeng, Jun Fu, Hadi Amirpour +5
Blind dehazed image quality assessment (BDQA), which aims to accurately predict the visual quality of dehazed images without any reference information, is essential for the evaluat…
Enhancing Incomplete Multi-modal Brain Tumor Segmentation with Intra-modal Asymmetry and Inter-modal Dependency
Weide Liu, Jingwen Hou, Xiaoyang Zhong +4
Deep learning-based brain tumor segmentation (BTS) models for multi-modal MRI images have seen significant advancements in recent years. However, a common problem in practice is th…
Adaptive Mixed-Scale Feature Fusion Network for Blind AI-Generated Image Quality Assessment
Tianwei Zhou, Songbai Tan, Wei Zhou +3
With the increasing maturity of the text-to-image and image-to-image generative models, AI-generated images (AGIs) have shown great application potential in advertisement, entertai…
Deep Bi-directional Attention Network for Image Super-Resolution Quality Assessment
Yixiao Li, Xiaoyuan Yang, Jun Fu +2
There has emerged a growing interest in exploring efficient quality assessment algorithms for image super-resolution (SR). However, employing deep learning techniques, especially d…