65 citations · 233 across the 23 of their papers we have counts for
28 papers · 1 filter
Deep Projective Rotation Estimation through Relative Supervision
Brian Okorn, Chuer Pan, Martial Hebert +1
Orientation estimation is the core to a variety of vision and robotics tasks such as camera and object pose estimation. Deep learning has offered a way to develop image-based orien…
Discovering Objects that Can Move
Zhipeng Bao, Pavel Tokmakov, Allan Jabri +3
This paper studies the problem of object discovery -- separating objects from the background without manual labels. Existing approaches utilize appearance cues, such as color, text…
Generative Modeling for Multi-task Visual Learning
Zhipeng Bao, Martial Hebert, Yu-Xiong Wang
Generative modeling has recently shown great promise in computer vision, but it has mostly focused on synthesizing visually realistic images. In this paper, motivated by multi-task…
Learning to Track Object Position through Occlusion
Satyaki Chakraborty, Martial Hebert
Occlusion is one of the most significant challenges encountered by object detectors and trackers. While both object detection and tracking has received a lot of attention in the pa…
ZePHyR: Zero-shot Pose Hypothesis Rating
Brian Okorn, Qiao Gu, Martial Hebert +1
Pose estimation is a basic module in many robot manipulation pipelines. Estimating the pose of objects in the environment can be useful for grasping, motion planning, or manipulati…
PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
Xia Chen, Jianren Wang, David Held +1
Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure.…