works on

From the 1 of 31 linked papers with an AI index.

activity
20242026
collaborators
Showing cs.CVShow all

26 papers · 1 filter

cs.CV2026

SIFT: Self-Imagination Fine-Tuning for Physically Plausible Motion in Video Diffusion Models

Ruoyu Wang, Jialun Liu, Huayang Huang +5

The paper introduces Self-Imagination Fine-Tuning (SIFT), a method that trains video diffusion models on their own generated videos to improve physical realism and disentangle moti…

cs.CV2026

RayRoPE: Projective Ray Positional Encoding for Multi-view Attention

Yu Wu, Minsik Jeon, Jen-Hao Rick Chang +2

We study positional encodings for multi-view transformers that process tokens from a set of posed input images, and seek a mechanism that encodes patches uniquely, allows SE(3)-inv…

cs.CV2026

Qwen-Image-2.0-RL Technical Report

Yixian Xu, Kaiyuan Gao, Yuxiang Chen +25

We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual qu…

cs.CV2026

Qwen-Image-VAE-2.0 Technical Report

Zekai Zhang, Deqing Li, Kuan Cao +27

We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…

cs.CV2026

Qwen-Image-2.0 Technical Report

Bing Zhao, Chenfei Wu, Deqing Li +72

We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…

cs.CV2026

SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation

Yuhan Pei, Ruoyu Wang, Yongqi Yang +3

Originating from the diffusion phenomenon in physics, which describes the random movement and collisions of particles, diffusion generative models simulate a random walk in the dat…