most citedUniVG-R1: Reasoning Guided Universal Visual Grounding with Reinforcement Learning

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cs.CV2026

Kairos: A Dataset for Fine-Grained Video-Language Modeling over Space, Time, and Dynamics

Ruibo Ming, Lei Sun, Deheng Zhang +8

Many emerging video language modeling tasks require systems to move beyond clip-level abstraction and model visual content as it unfolds over extended time horizons. However, most…

cs.CV2026

Geometry-Aware Test-Time Learning for Quantitative Spatial Reasoning

Gege Zhang, Shuaicheng Niu, Gang Dai +2

Quantitative spatial reasoning in visual-language models (VLMs) aims to infer spatial distances and directional relationships among objects in 3D space from a 2D image and a natura…

cs.CV2026

Evaluation-Verification Reward for Consistent Multi-Reference Image Editing

Yingmao Miao, Pengfei Zhang, Xiaochen Lv +5

While recent image editing models have made rapid progress, multi-reference editing remains challenging, particularly in maintaining visual consistency across references and ensuri…

cs.CV2026

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment

Geng Li, Haiwen Li, Rui Chen +3

Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks. Its progress is hindered n…

cs.CV2026

DreamX-World 1.0: A General-Purpose Interactive World Model

DreamX Team, Yancheng Bai, Rui Chen +20

DreamX-World 1.0 is a general-purpose interactive text/image-to-video world model for controllable long-horizon generation. It supports camera navigation, revisits to previously ob…

cs.CV2026

Elucidating the SNR-t Bias of Diffusion Probabilistic Models

Meng Yu, Lei Sun, Jianhao Zeng +2

Diffusion Probabilistic Models have demonstrated remarkable performance across a wide range of generative tasks. However, we have observed that these models often suffer from a Sig…