4 papers
KungfuAthleteBot: learning high-dynamic humanoid motion from video with unified robust recovery
Zhongxiang Lei, Lulu Cao, Xuyang Wang +3
Video is an abundant, inexpensive source of human motion data that is rich in extreme athletic behaviors. Making it usable for humanoid robots, however, is not a matter of simply r…
KungfuAthleteBot: Learning High-Dynamic Motion from Videos with Unified Robust Recovery
Zhongxiang Lei, Lulu Cao, Xuyang Wang +3
Learning highly dynamic motions from video provides a scalable alternative to expensive data collection for humanoid robots, yet it is challenged by height floating, missing kinema…
Prompt-Guided Dual-Path UNet with Mamba for Medical Image Segmentation
Shaolei Zhang, Jinyan Liu, Tianyi Qian +1
Convolutional neural networks (CNNs) and transformers are widely employed in constructing UNet architectures for medical image segmentation tasks. However, CNNs struggle to model l…
Neural Radiance Fields for the Real World: A Survey
Wenhui Xiao, Remi Chierchia, Rodrigo Santa Cruz +5
Neural Radiance Fields (NeRFs) have remodeled 3D scene representation since release. NeRFs can effectively reconstruct complex 3D scenes from 2D images, advancing different fields…