13 citations · 22 across the 46 of their papers we have counts for
9 papers · 1 filter
Distractor-free Generalizable 3D Gaussian Splatting
Yanqi Bao, Jing Liao, Jing Huo +1
We present DGGS, a novel framework that addresses the previously unexplored challenge: (3DGS). It mitigates 3D incons…
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
Mingzhi Wang, Chengdong Ma, Qizhi Chen +7
Self-play methods have demonstrated remarkable success in enhancing model capabilities across various domains. In the context of Reinforcement Learning from Human Feedback (RLHF),…
GravMAD: Grounded Spatial Value Maps Guided Action Diffusion for Generalized 3D Manipulation
Yangtao Chen, Zixuan Chen, Junhui Yin +4
Robots' ability to follow language instructions and execute diverse 3D manipulation tasks is vital in robot learning. Traditional imitation learning-based methods perform well on s…
3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities
Yanqi Bao, Tianyu Ding, Jing Huo +5
3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view i…
Training-Free Video Editing via Optical Flow-Enhanced Score Distillation
Lianghan Zhu, Yanqi Bao, Jing Huo +4
The rapid advancement in visual generation, particularly the emergence of pre-trained text-to-image and text-to-video models, has catalyzed growing interest in training-free video…
Analogist: Out-of-the-box Visual In-Context Learning with Image Diffusion Model
Zheng Gu, Shiyuan Yang, Jing Liao +2
Visual In-Context Learning (ICL) has emerged as a promising research area due to its capability to accomplish various tasks with limited example pairs through analogical reasoning.…
ONNXPruner: ONNX-Based General Model Pruning Adapter
Dongdong Ren, Wenbin Li, Tianyu Ding +5
Recent advancements in model pruning have focused on developing new algorithms and improving upon benchmarks. However, the practical application of these algorithms across various…
Exploiting Inter-sample and Inter-feature Relations in Dataset Distillation
Wenxiao Deng, Wenbin Li, Tianyu Ding +5
Dataset distillation has emerged as a promising approach in deep learning, enabling efficient training with small synthetic datasets derived from larger real ones. Particularly, di…
Stitching, Fine-tuning, Re-training: A SAM-enabled Framework for Semi-supervised 3D Medical Image Segmentation
Shumeng Li, Lei Qi, Qian Yu +3
Segment Anything Model (SAM) fine-tuning has shown remarkable performance in medical image segmentation in a fully supervised manner, but requires precise annotations. To reduce th…