activity
20182020
most citedState Alignment-based Imitation Learning

18 citations · 46 across the 8 of their papers we have counts for

collaborators

16 papers

cs.GR2020

Photon-Driven Neural Path Guiding

Shilin Zhu, Zexiang Xu, Tiancheng Sun +5

Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving c…

cs.CV20205 cited

Weakly-supervised 3D Shape Completion in the Wild

Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam +5

3D shape completion for real data is important but challenging, since partial point clouds acquired by real-world sensors are usually sparse, noisy and unaligned. Different from pr…

cs.CV2020

Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints

You-Yi Jau, Rui Zhu, Hao Su +1

Estimating relative camera poses from consecutive frames is a fundamental problem in visual odometry (VO) and simultaneous localization and mapping (SLAM), where classic methods co…

cs.CV2020

Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance

Minghua Liu, Xiaoshuai Zhang, Hao Su

We are interested in reconstructing the mesh representation of object surfaces from point clouds. Surface reconstruction is a prerequisite for downstream applications such as rende…

cs.GR20201 cited

Deep Photon Mapping

Shilin Zhu, Zexiang Xu, Henrik Wann Jensen +2

Recently, deep learning-based denoising approaches have led to dramatic improvements in low sample-count Monte Carlo rendering. These approaches are aimed at path tracing, which is…

cs.LG201918 cited

State Alignment-based Imitation Learning

Fangchen Liu, Zhan Ling, Tongzhou Mu +1

Consider an imitation learning problem that the imitator and the expert have different dynamics models. Most of the current imitation learning methods fail because they focus on im…