297 citations · 1.1k across the 40 of their papers we have counts for
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ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape
Fabian Manhardt, Wadim Kehl, Adrien Gaidon
We present a deep learning method for end-to-end monocular 3D object detection and metric shape retrieval. We propose a novel loss formulation by lifting 2D detection, orientation,…
Learning to Fuse Things and Stuff
Jie Li, Allan Raventos, Arjun Bhargava +2
We propose an end-to-end learning approach for panoptic segmentation, a novel task unifying instance (things) and semantic (stuff) segmentation. Our model, TASCNet, uses feature ma…
SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation
Sudeep Pillai, Rares Ambrus, Adrien Gaidon
Recent techniques in self-supervised monocular depth estimation are approaching the performance of supervised methods, but operate in low resolution only. We show that high resolut…
SPIGAN: Privileged Adversarial Learning from Simulation
Kuan-Hui Lee, German Ros, Jie Li +1
Deep Learning for Computer Vision depends mainly on the source of supervision.Photo-realistic simulators can generate large-scale automatically labeled syntheticdata, but introduce…