activity
20242026
most citedCATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution

3 citations · 5 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2026

Enabling Proactive Spoken Turns via a Generalized Style-Aware Full-Duplex Framework

Tianrui Pan, Qinglin Zhang, Chong Deng +6

Compared with half-duplex dialogue systems where the system waits for user turn completion before it responds, natural full-duplex dialogue systems require agents to act proactivel…

cs.CV2026

Disentangled Textual Priors for Diffusion-based Image Super-Resolution

Lei Jiang, Xin Liu, Xinze Tong +4

Image Super-Resolution (SR) aims to reconstruct high-resolution images from degraded low-resolution inputs. While diffusion-based SR methods offer powerful generative capabilities,…

cs.CV2026

GLAD: Generative Language-Assisted Visual Tracking for Low-Semantic Templates

Xingyu Luo, Yidong Cai, Jie Liu +3

Vision-language tracking has gained increasing attention in many scenarios. This task simultaneously deals with visual and linguistic information to localize objects in videos. Des…

cs.SD2025

Towards Practical Real-Time Low-Latency Music Source Separation

Junyu Wu, Jie Liu, Tianrui Pan +2

In recent years, significant progress has been made in the field of deep learning for music demixing. However, there has been limited attention on real-time, low-latency music demi…

cs.CV2025

ObjFiller3D: Scaling 3D Object Inpainting to Dense Multi-View Consistency

Haitang Feng, Xinkai Chen, Jie Liu +5

3D object inpainting is commonly achieved via multi-view 2D image completion, yet independently inpainted views often suffer from cross-view inconsistencies, leading to blurred tex…

cs.CV2025

RASR: Retrieval-Augmented Super Resolution for Practical Reference-based Image Restoration

Jiaqi Yan, Shuning Xu, Xiangyu Chen +5

Reference-based Super Resolution (RefSR) improves upon Single Image Super Resolution (SISR) by leveraging high-quality reference images to enhance texture fidelity and visual reali…