39 citations · 43 across the 4 of their papers we have counts for
4 papers
Progressive Volume Distillation with Active Learning for Efficient NeRF Architecture Conversion
Shuangkang Fang, Yufeng Wang, Yi Yang +4
Neural Radiance Fields (NeRF) have been widely adopted as practical and versatile representations for 3D scenes, facilitating various downstream tasks. However, different architect…
OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion
Ruihang Miao, Weizhou Liu, Mingrui Chen +4
3D Semantic Scene Completion (SSC) can provide dense geometric and semantic scene representations, which can be applied in the field of autonomous driving and robotic systems. It i…
One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation
Shuangkang Fang, Weixin Xu, Heng Wang +3
Neural Radiance Fields (NeRF) methods have proved effective as compact, high-quality and versatile representations for 3D scenes, and enable downstream tasks such as editing, retri…
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Weixin Xu, Zipeng Feng, Shuangkang Fang +3
Vast requirement of computation power of Deep Neural Networks is a major hurdle to their real world applications. Many recent Application Specific Integrated Circuit (ASIC) chips f…