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20202026
most citedA Topic-Attentive Transformer-based Model For Multimodal Depression Detection

8 citations · 19 across the 14 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

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…

cs.CV2026

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2023

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…

cs.CV2021

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.…

cs.CV2021★ 1 cited

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…

cs.CV2021

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.…

cs.CV2021★ 6 cited

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…

cs.CV2020★ 2 cited

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…