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20232026
most citedTowards Distribution-Agnostic Generalized Category Discovery

2 citations · 5 across the 17 of their papers we have counts for

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cs.CV2026

D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation

Wenjie Zheng, Haoji Hu, Jiali Lu +2

Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing studies mainly focus on image clas…

cs.CV2026

Q Cache: Visual Attention is Valuable in Less than Half of Decode Layers for Multimodal Large Language Model

Jiedong Zhuang, Lu Lu, Ming Dai +4

Multimodal large language models (MLLMs) are plagued by exorbitant inference costs attributable to the profusion of visual tokens within the vision encoder. The redundant visual to…

cs.CV2025

SemanticGen: Video Generation in Semantic Space

Jianhong Bai, Xiaoshi Wu, Xintao Wang +9

State-of-the-art video generative models typically learn the distribution of video latents in the VAE space and map them to pixels using a VAE decoder. While this approach can gene…

cs.CV2025

Training-Free Multi-View Extension of IC-Light for Textual Position-Aware Scene Relighting

Jiangnan Ye, Jiedong Zhuang, Lianrui Mu +5

We introduce GS-Light, an efficient, textual position-aware pipeline for text-guided relighting of 3D scenes represented via Gaussian Splatting (3DGS). GS-Light implements a traini…

cs.CV2025

No Pixel Left Behind: A Detail-Preserving Architecture for Robust High-Resolution AI-Generated Image Detection

Lianrui Mu, Zou Xingze, Jianhong Bai +7

The rapid growth of high-resolution, meticulously crafted AI-generated images poses a significant challenge to existing detection methods, which are often trained and evaluated on…

cs.CV2025

ReCamMaster: Camera-Controlled Generative Rendering from A Single Video

Jianhong Bai, Menghan Xia, Xiao Fu +8

Camera control has been actively studied in text or image conditioned video generation tasks. However, altering camera trajectories of a given video remains under-explored, despite…