Amodal ground truth and completion in the wild
This paper studies amodal image segmentation: predicting entire object segmentation
masks including both visible and invisible (occluded) parts. In previous work the amodal …
masks including both visible and invisible (occluded) parts. In previous work the amodal …
TARGO: Benchmarking Target-driven Object Grasping under Occlusions
Recent advances in predicting 6D grasp poses from a single depth image have led to
promising performance in robotic grasping. However, previous grasping models face …
promising performance in robotic grasping. However, previous grasping models face …
Amodal Depth Anything: Amodal Depth Estimation in the Wild
Amodal depth estimation aims to predict the depth of occluded (invisible) parts of objects in
a scene. This task addresses the question of whether models can effectively perceive the …
a scene. This task addresses the question of whether models can effectively perceive the …
Predicting Traffic Congestion at Urban Intersections Using Data-Driven Modeling
T Kelly, J Gupta - arXiv preprint arXiv:2404.08838, 2024 - arxiv.org
Traffic congestion at intersections is a significant issue in urban areas, leading to increased
commute times, safety hazards, and operational inefficiencies. This study aims to develop a …
commute times, safety hazards, and operational inefficiencies. This study aims to develop a …