430 citations · 1.2k across the 77 of their papers we have counts for
9 papers · 1 filter
PEANUT: Predicting and Navigating to Unseen Targets
Albert J. Zhai, Shenlong Wang
Efficient ObjectGoal navigation (ObjectNav) in novel environments requires an understanding of the spatial and semantic regularities in environment layouts. In this work, we presen…
QFF: Quantized Fourier Features for Neural Field Representations
Jae Yong Lee, Yuqun Wu, Chuhang Zou +2
Multilayer perceptrons (MLPs) learn high frequencies slowly. Recent approaches encode features in spatial bins to improve speed of learning details, but at the cost of larger model…
DiffTune: Hyperparameter-Free Auto-Tuning using Auto-Differentiation
Sheng Cheng, Lin Song, Minkyung Kim +2
Controller tuning is a vital step to ensure the controller delivers its designed performance. DiffTune has been proposed as an automatic tuning method that unrolls the dynamical sy…
CASA: Category-agnostic Skeletal Animal Reconstruction
Yuefan Wu, Zeyuan Chen, Shaowei Liu +2
Recovering the skeletal shape of an animal from a monocular video is a longstanding challenge. Prevailing animal reconstruction methods often adopt a control-point driven animation…
ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field
Yuan Li, Zhi-Hao Lin, David Forsyth +2
Physical simulations produce excellent predictions of weather effects. Neural radiance fields produce SOTA scene models. We describe a novel NeRF-editing procedure that can fuse ph…
Learning to Generate Realistic LiDAR Point Clouds
Vlas Zyrianov, Xiyue Zhu, Shenlong Wang
We present LiDARGen, a novel, effective, and controllable generative model that produces realistic LiDAR point cloud sensory readings. Our method leverages the powerful score-match…