1.4k citations · 3.1k across the 72 of their papers we have counts for
10 papers · 1 filter
Self-supervised Object Motion and Depth Estimation from Video
Qi Dai, Vaishakh Patil, Simon Hecker +3
We present a self-supervised learning framework to estimate the individual object motion and monocular depth from video. We model the object motion as a 6 degree-of-freedom rigid-b…
Semantic Understanding of Foggy Scenes with Purely Synthetic Data
Martin Hahner, Dengxin Dai, Christos Sakaridis +2
This work addresses the problem of semantic scene understanding under foggy road conditions. Although marked progress has been made in semantic scene understanding over the recent…
Talk2Nav: Long-Range Vision-and-Language Navigation with Dual Attention and Spatial Memory
Arun Balajee Vasudevan, Dengxin Dai, Luc Van Gool
The role of robots in society keeps expanding, bringing with it the necessity of interacting and communicating with humans. In order to keep such interaction intuitive, we provide…
Texture Underfitting for Domain Adaptation
Jan-Nico Zaech, Dengxin Dai, Martin Hahner +1
Comprehensive semantic segmentation is one of the key components for robust scene understanding and a requirement to enable autonomous driving. Driven by large scale datasets, conv…
Learning a Curve Guardian for Motorcycles
Simon Hecker, Alexander Liniger, Henrik Maurenbrecher +2
Up to 17% of all motorcycle accidents occur when the rider is maneuvering through a curve and the main cause of curve accidents can be attributed to inappropriate speed and wrong i…
Gated CRF Loss for Weakly Supervised Semantic Image Segmentation
Anton Obukhov, Stamatios Georgoulis, Dengxin Dai +1
State-of-the-art approaches for semantic segmentation rely on deep convolutional neural networks trained on fully annotated datasets, that have been shown to be notoriously expensi…
Learning Accurate, Comfortable and Human-like Driving
Simon Hecker, Dengxin Dai, Luc Van Gool
Autonomous vehicles are more likely to be accepted if they drive accurately, comfortably, but also similar to how human drivers would. This is especially true when autonomous and h…
Real-time 3D Traffic Cone Detection for Autonomous Driving
Ankit Dhall, Dengxin Dai, Luc Van Gool
Considerable progress has been made in semantic scene understanding of road scenes with monocular cameras. It is, however, mainly related to certain classes such as cars and pedest…
Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation
Christos Sakaridis, Dengxin Dai, Luc Van Gool
Most progress in semantic segmentation reports on daytime images taken under favorable illumination conditions. We instead address the problem of semantic segmentation of nighttime…
Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding
Dengxin Dai, Christos Sakaridis, Simon Hecker +1
This work addresses the problem of semantic scene understanding under fog. Although marked progress has been made in semantic scene understanding, it is mainly concentrated on clea…