6 papers
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…
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…
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…
Searching Priors Makes Text-to-Video Synthesis Better
Haoran Cheng, Liang Peng, Linxuan Xia +5
Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle t…
Regulating Intermediate 3D Features for Vision-Centric Autonomous Driving
Junkai Xu, Liang Peng, Haoran Cheng +6
Multi-camera perception tasks have gained significant attention in the field of autonomous driving. However, existing frameworks based on Lift-Splat-Shoot (LSS) in the multi-camera…
SmoothVideo: Smooth Video Synthesis with Noise Constraints on Diffusion Models for One-shot Video Tuning
Liang Peng, Haoran Cheng, Zheng Yang +6
Recent one-shot video tuning methods, which fine-tune the network on a specific video based on pre-trained text-to-image models (e.g., Stable Diffusion), are popular in the communi…