1.4k citations · 2.6k across the 155 of their papers we have counts for
6 papers · 2 filters
Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images
Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli +1
Image features for retrieval-based localization must be invariant to dynamic objects (e.g. cars) as well as seasonal and daytime changes. Such invariances are, up to some extent, l…
Automated Search for Resource-Efficient Branched Multi-Task Networks
David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis +1
The multi-modal nature of many vision problems calls for neural network architectures that can perform multiple tasks concurrently. Typically, such architectures have been handcraf…
Self-Calibration Supported Robust Projective Structure-from-Motion
Rui Gong, Danda Pani Paudel, Ajad Chhatkuli +1
Typical Structure-from-Motion (SfM) pipelines rely on finding correspondences across images, recovering the projective structure of the observed scene and upgrading it to a metric…
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation
Christos Sakaridis, Dengxin Dai, Luc Van Gool
We address the problem of semantic nighttime image segmentation and improve the state-of-the-art, by adapting daytime models to nighttime without using nighttime annotations. Moreo…
Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network
Dario Kneubuehler, Shuhang Gu, Luc Van Gool +1
We propose the first practical multitask image enhancement network, that is able to learn one-to-many and many-to-one image mappings. We show that our model outperforms the current…
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video
Vaishakh Patil, Wouter Van Gansbeke, Dengxin Dai +1
Autonomous cars need continuously updated depth information. Thus far, depth is mostly estimated independently for a single frame at a time, even if the method starts from video in…