8 citations · 19 across the 14 of their papers we have counts for
15 papers
Dynamic Interpolation for Training-Time Prediction Reshaping in Low-Light Image Enhancement
Peirui Zhu, Shijie Hao, Jingxi Liao +2
Low-light image enhancement (LLIE) is an important image/video processing problem for reliable visual systems under poor illumination, yet it remains challenging due to the strong…
NOUS: Video-Driven 3D Human Reaction Generation via Observation-Reaction Mutual Steering
Yuan Zhou, Luanyuan Dai, Yongzhi Li +7
Video-driven 3D human reaction generation aims to synthesize 3D human motion in response to the action observed in a video, playing an important role in interactive multimedia syst…
Biomedical Relation Extraction via Adaptive Document-Relation Cross-Mapping and Concept Unique Identifier
Yufei Shang, Yanrong Guo, Shijie Hao +1
Document-Level Biomedical Relation Extraction (Bio-RE) aims to identify relations between biomedical entities within extensive texts, serving as a crucial subfield of biomedical te…
InterMind: Doctor-Patient-Family Interactive Depression Assessment Empowered by Large Language Models
Zhiyuan Zhou, Jilong Liu, Sanwang Wang +3
Depression poses significant challenges to patients and healthcare organizations, necessitating efficient assessment methods. Existing paradigms typically focus on a patient-doctor…
SDI-Net: Toward Sufficient Dual-View Interaction for Low-light Stereo Image Enhancement
Linlin Hu, Ao Sun, Shijie Hao +2
Currently, most low-light image enhancement methods only consider information from a single view, neglecting the correlation between cross-view information. Therefore, the enhancem…
Controllable Relation Disentanglement for Few-Shot Class-Incremental Learning
Yuan Zhou, Richang Hong, Yanrong Guo +3
In this paper, we propose to tackle Few-Shot Class-Incremental Learning (FSCIL) from a new perspective, i.e., relation disentanglement, which means enhancing FSCIL via disentanglin…
Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation
Yuan Zhou, Xin Chen, Yanrong Guo +3
Incremental few-shot semantic segmentation (IFSS) aims to incrementally extend a semantic segmentation model to novel classes according to only a few pixel-level annotated data, wh…
A Topic-Attentive Transformer-based Model For Multimodal Depression Detection
Yanrong Guo, Chenyang Zhu, Shijie Hao +1
Depression is one of the most common mental disorders, which imposes heavy negative impacts on one's daily life. Diagnosing depression based on the interview is usually in the form…
Automatic Depression Detection via Learning and Fusing Features from Visual Cues
Yanrong Guo, Chenyang Zhu, Shijie Hao +1
Depression is one of the most prevalent mental disorders, which seriously affects one's life. Traditional depression diagnostics commonly depends on rating with scales, which can b…
Decoupled Low-light Image Enhancement
Shijie Hao, Xu Han, Yanrong Guo +1
The visual quality of photographs taken under imperfect lightness conditions can be degenerated by multiple factors, e.g., low lightness, imaging noise, color distortion and so on.…
Few-shot Learning with Global Relatedness Decoupled-Distillation
Yuan Zhou, Yanrong Guo, Shijie Hao +3
Despite the success that metric learning based approaches have achieved in few-shot learning, recent works reveal the ineffectiveness of their episodic training mode. In this paper…
Few-shot Partial Multi-view Learning
Yuan Zhou, Yanrong Guo, Shijie Hao +2
It is often the case that data are with multiple views in real-world applications. Fully exploring the information of each view is significant for making data more representative.…
Positive Sample Propagation along the Audio-Visual Event Line
Jinxing Zhou, Liang Zheng, Yiran Zhong +2
Visual and audio signals often coexist in natural environments, forming audio-visual events (AVEs). Given a video, we aim to localize video segments containing an AVE and identify…
A Survey on Large-scale Machine Learning
Meng Wang, Weijie Fu, Xiangnan He +2
Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining…
Real-time Semantic Segmentation via Spatial-detail Guided Context Propagation
Shijie Hao, Yuan Zhou, Yanrong Guo +3
Nowadays, vision-based computing tasks play an important role in various real-world applications. However, many vision computing tasks, e.g. semantic segmentation, are usually comp…