133 citations · 180 across the 14 of their papers we have counts for
16 papers · 1 filter
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…
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…
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…
TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation
Xiaopei Wu, Yuenan Hou, Xiaoshui Huang +8
Training deep models for LiDAR semantic segmentation is challenging due to the inherent sparsity of point clouds. Utilizing temporal data is a natural remedy against the sparsity p…