most citedAB-Cache: Training-Free Acceleration of Diffusion Models via Adams-Bashforth Cached Feature Reuse

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cs.CV2026

Beyond Text Prompts: Visual-to-Visual Generation as A Unified Paradigm

Yaofang Liu, Kangning Cui, Meng Chu +7

Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generators still ask users to seria…

cs.CV2026

Seg-Agent: Test-Time Multimodal Reasoning for Training-Free Language-Guided Segmentation

Chao Hao, Jun Xu, Ji Du +6

Language-guided segmentation transcends the scope limitations of traditional semantic segmentation, enabling models to segment arbitrary target regions based on natural language in…

cs.CV2026

CutClaw: Agentic Hours-Long Video Editing via Music Synchronization

Shifang Zhao, Yihan Hu, Ying Shan +2

Editing the video content with audio alignment forms a digital human-made art in current social media. However, the time-consuming and repetitive nature of manual video editing has…

cs.CV2026

LightCtrl: Training-free Controllable Video Relighting

Yizuo Peng, Xuelin Chen, Kai Zhang +1

Recent diffusion models have achieved remarkable success in image relighting, and this success has quickly been extended to video relighting. However, existing methods offer limite…

cs.CV2026

MLLM-4D: Towards Visual-based Spatial-Temporal Intelligence

Xingyilang Yin, Chengzhengxu Li, Jiahao Chang +2

Humans are born with vision-based 4D spatial-temporal intelligence, which enables us to perceive and reason about the evolution of 3D space over time from purely visual inputs. Des…

cs.CV2025

EasyOmnimatte: Taming Pretrained Inpainting Diffusion Models for End-to-End Video Layered Decomposition

Yihan Hu, Xuelin Chen, Xiaodong Cun

Existing video omnimatte methods typically rely on slow, multi-stage, or inference-time optimization pipelines that fail to fully exploit powerful generative priors, producing subo…