The robodrive challenge: Drive anytime anywhere in any condition

L Kong, S **e, H Hu, Y Niu, WT Ooi… - arxiv preprint arxiv …, 2024 - arxiv.org
In the realm of autonomous driving, robust perception under out-of-distribution conditions is
paramount for the safe deployment of vehicles. Challenges such as adverse weather …

The third monocular depth estimation challenge

J Spencer, F Tosi, M Poggi, RS Arora… - Proceedings of the …, 2024 - openaccess.thecvf.com
This paper discusses the results of the third edition of the Monocular Depth Estimation
Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging …

The second monocular depth estimation challenge

J Spencer, CS Qian, M Trescakova… - Proceedings of the …, 2023 - openaccess.thecvf.com
This paper discusses the results for the second edition of the Monocular Depth Estimation
Challenge (MDEC). This edition was open to methods using any form of supervision …

The robodepth challenge: Methods and advancements towards robust depth estimation

L Kong, Y Niu, S **e, H Hu, LX Ng… - arxiv preprint arxiv …, 2023 - arxiv.org
Accurate depth estimation under out-of-distribution (OoD) scenarios, such as adverse
weather conditions, sensor failure, and noise contamination, is desirable for safety-critical …

Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Fail

L Bartolomei, F Tosi, M Poggi, S Mattoccia - arxiv preprint arxiv …, 2024 - arxiv.org
We introduce Stereo Anywhere, a novel stereo-matching framework that combines
geometric constraints with robust priors from monocular depth Vision Foundation Models …

The second monocular depth estimation challenge: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

CS Qian, M Trescakova, C Russell, S Hadfield… - 2023 - eprints.soton.ac.uk
This paper discusses the results for the second edition of the Monocular Depth Estimation
Challenge (MDEC). This edition was open to methods using any form of supervision …

The Second Monocular Depth Estimation Challenge

JS Martin, CS Qian, C Russell… - 2023 IEEE/CVF … - openresearch.surrey.ac.uk
This paper discusses the results for the second edition of the Monocular Depth Estimation
Challenge (MDEC). This edition was open to methods using any form of supervision …