Search Results for author:
Found 5 papers, 3 papers with code
SeekNet: Improved Human Instance Segmentation via Reinforcement Learning Based Optimized Robot Relocation
Amodal recognition is the ability of the system to detect occluded objects.
Learning Panoptic Segmentation from Instance Contours
Instance contours along with semantic segmentation yield a boundary aware semantic segmentation of things.
ProxEmo: Gait-based Emotion Learning and Multi-view Proxemic Fusion for Socially-Aware Robot Navigation
Our approach predicts the perceived emotions of a pedestrian from walking gaits, which is then used for emotion-guided navigation taking into account social and proxemic constraints.
Ranked #1 on
Emotion Classification
on EWALK
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
We conduct extensive experiments on our YCB-Video dataset and the OccludedLINEMOD dataset to show that PoseCNN is highly robust to occlusions, can handle symmetric objects, and provide accurate pose estimation using only color images as input.
Ranked #3 on
6D Pose Estimation using RGBD
on YCB-Video
PERCH: Perception via Search for Multi-Object Recognition and Localization
In many robotic domains such as flexible automated manufacturing or personal assistance, a fundamental perception task is that of identifying and localizing objects whose 3D models are known.
