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cs.CV2025

Any-to-Bokeh: Arbitrary-Subject Video Refocusing with Video Diffusion Model

Yang Yang, Siming Zheng, Qirui Yang +6

Diffusion models have recently emerged as powerful tools for camera simulation, enabling both geometric transformations and realistic optical effects. Among these, image-based boke…

cs.CV2025

SUDO: Enhancing Text-to-Image Diffusion Models with Self-Supervised Direct Preference Optimization

Liang Peng, Boxi Wu, Haoran Cheng +2

Previous text-to-image diffusion models typically employ supervised fine-tuning (SFT) to enhance pre-trained base models. However, this approach primarily minimizes the loss of mea…

cs.CV2025

Discriminator-Free Direct Preference Optimization for Video Diffusion

Haoran Cheng, Qide Dong, Liang Peng +7

Direct Preference Optimization (DPO), which aligns models with human preferences through win/lose data pairs, has achieved remarkable success in language and image generation. Howe…

cs.CV2025

PersonalVideo: High ID-Fidelity Video Customization without Dynamic and Semantic Degradation

Hengjia Li, Haonan Qiu, Shiwei Zhang +6

The current text-to-video (T2V) generation has made significant progress in synthesizing realistic general videos, but it is still under-explored in identity-specific human video g…

cs.CV2024

GCA-3D: Towards Generalized and Consistent Domain Adaptation of 3D Generators

Hengjia Li, Yang Liu, Yibo Zhao +9

Recently, 3D generative domain adaptation has emerged to adapt the pre-trained generator to other domains without collecting massive datasets and camera pose distributions. Typical…

cs.CV2024

Local Conditional Controlling for Text-to-Image Diffusion Models

Yibo Zhao, Liang Peng, Yang Yang +9

Diffusion models have exhibited impressive prowess in the text-to-image task. Recent methods add image-level structure controls, e.g., edge and depth maps, to manipulate the genera…