43 citations · 47 across the 9 of their papers we have counts for
12 papers · 1 filter
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…
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…
Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs
Yanqi Bao, Yuxin Li, Jing Huo +4
Neural Radiance Fields from Sparse input} (NeRF-S) have shown great potential in synthesizing novel views with a limited number of observed viewpoints. However, due to the inherent…
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo +3
Generalizing Neural Radiance Fields (NeRF) to new scenes is a significant challenge that existing approaches struggle to address without extensive modifications to vanilla NeRF fra…
A Unified Framework for Contrastive Learning from a Perspective of Affinity Matrix
Wenbin Li, Meihao Kong, Xuesong Yang +4
In recent years, a variety of contrastive learning based unsupervised visual representation learning methods have been designed and achieved great success in many visual tasks. Gen…