activity
20232026
most citedDigging into contrastive learning for robust depth estimation with diffusion models

7 citations · 8 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters

Honglie Wang, Jia Sun, Zijun Li +11

Text editing in product posters entails inserting new text or replacing existing text while preserving product appearance, background content, and global composition. Despite recen…

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

RePer-360: Releasing Perspective Priors for 360 Depth Estimation via Self-Modulation

Cheng Guan, Chunyu Lin, Zhijie Shen +2

Recent depth foundation models trained on perspective imagery achieve strong performance, yet generalize poorly to 360 images due to the substantial geometric discrepancy b…

cs.CV2026

Edit in 2D, Verify in 3D: Reinforcement Learning for Multi-view Consistent Scene Editing

Jiyuan Wang, Chunyu Lin, Lei Sun +8

Leveraging the priors of 2D diffusion models for 3D editing has emerged as a promising paradigm. However, multi-view consistency remains challenging in edited results, and the extr…