6 citations · 13 across the 6 of their papers we have counts for
6 papers
Mono-STAR: Mono-camera Scene-level Tracking and Reconstruction
Haonan Chang, Dhruv Metha Ramesh, Shijie Geng +2
We present Mono-STAR, the first real-time 3D reconstruction system that simultaneously supports semantic fusion, fast motion tracking, non-rigid object deformation, and topological…
Scene-level Tracking and Reconstruction without Object Priors
Haonan Chang, Abdeslam Boularias
We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the…
Cascade Attribute Network: Decomposing Reinforcement Learning Control Policies using Hierarchical Neural Networks
Haonan Chang, Zhuo Xu, Masayoshi Tomizuka
Reinforcement learning methods have been developed to achieve great success in training control policies in various automation tasks. However, a main challenge of the wider applica…
GeoFusion: Geometric Consistency informed Scene Estimation in Dense Clutter
Zhiqiang Sui, Haonan Chang, Ning Xu +1
We propose GeoFusion, a SLAM-based scene estimation method for building an object-level semantic map in dense clutter. In dense clutter, objects are often in close contact and seve…
GlassLoc: Plenoptic Grasp Pose Detection in Transparent Clutter
Zheming Zhou, Tianyang Pan, Shiyu Wu +2
Transparent objects are prevalent across many environments of interest for dexterous robotic manipulation. Such transparent material leads to considerable uncertainty for robot per…
Cascade Attribute Learning Network
Zhuo Xu, Haonan Chang, Masayoshi Tomizuka
We propose the cascade attribute learning network (CALNet), which can learn attributes in a control task separately and assemble them together. Our contribution is twofold: first w…