3 papers
cs.CV2026
DetailAnywhere: Fashion Detail Generation via Cross-Modal Feature Alignment Distillation
Zijun Li, Yimin Zhou, Jia Sun +12
Diffusion-based generative AI has achieved remarkable success in e-commerce applications such as virtual try-on, poster generation, and product background synthesis. However, when…
cs.CV2026
CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
Jiyuan Wang, Huan Ouyang, Jiuzhou Lin +15
In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it first conducts a global tem…
cs.CV2026
EVE: Verifiable Self-Evolution of MLLMs via Executable Visual Transformations
Yongrui Heng, Chaoya Jiang, Han Yang +2
Self-evolution of multimodal large language models (MLLMs) remains a critical challenge: pseudo-label-based methods suffer from progressive quality degradation as model predictions…