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cs.CV2026

FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models

Zihan Meng, Weidong Chen, Dexiang Hong +2

Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce this cost through similarity-ba…

cs.CV2026

LoViF 2026 The First Challenge on Unified Removal of Raindrops and Reflections: Methods and Results

Zewei He, Xi Tong, Yu Chen +49

This workshop paper comprehensively reviews the First Challenge on Unified Removal of Raindrops and Reflections. The challenge aims to address a frequently encountered practical pr…

cs.CV2026

The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

Xiang Chen, Hao Li, Jiangxin Dong +89

This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image restoration under diverse real-wo…

cs.CV2026

EmoStyle: Affective Conditioning of Style-Specialist Experts for Emotional Image Generation

Dexiang Hong, Yijie Guo, Weidong Chen +4

Emotion-aware artistic image generation requires an image to match the input prompt, follow the specified artistic style, and convey the target emotion. In this challenge, the main…

cs.CV2026

Audio-Visual Exchange-Aware Token Pruning for Efficient Audio-Visual Captioning

Zihan Meng, Dexiang Hong, Weidong Chen +3

Audio-visual captioning generates natural language descriptions from video and audio content. Multimodal LLMs have advanced this task, but both modalities contribute many tokens to…

cs.CV2026

CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers

Weidong Chen, Dexiang Hong, Zhendong Mao +4

Graphic design images consist of multiple editable layers, such as text, background, and decorative elements, while most generative models produce rasterized outputs without explic…