Robust Vision Challenge

Robust Vision Challenge 2020

The increasing availability of large annotated datasets such as Middlebury, PASCAL VOC, ImageNet, MS COCO, KITTI and Cityscapes has lead to tremendous progress in computer vision and machine learning over the last decade. Public leaderboards make it easy to track the state-of-the-art in the field by comparing the results of dozens of methods side-by-side. While steady progress is made on each individual dataset, many of them are limited to specific domains. KITTI, for example, focuses on real-world urban driving scenarios, while Middlebury considers indoor scenes. Consequently, methods that are state-of-the-art on one dataset often perform worse on a different one or require substantial adaptation of the model parameters.

The goal of this challenge is to foster the development of vision systems that are robust and consequently perform well on a variety of datasets with different characteristics. Towards this goal, we propose the Robust Vision Challenge, where performance on several tasks (eg, reconstruction, optical flow, semantic/instance segmentation, single image depth prediction) is measured across a number of challenging benchmarks with different characteristics, e.g., indoors vs. outdoors, real vs. synthetic, sunny vs. bad weather, different sensors. We encourage submissions of novel algorithms, techniques which are currently in review and methods that have already been published.

Questions? Please see the Submit Results page for anwsers regarding the RVC rules.

Prizes for winner and the runner-up of each of the seven challenges:

1st Place: $1200

2nd Place: $600

Presentation at our
ECCV 2020 Workshop

Challenges

RVC 2020 features seven challenges: stereo, optical flow, single image depth prediction, object detection, semantic segmentation, instance segmentation, and panoptic segmentation. Participants are free to submit to a single challenge or to multiple challenges. For each challenge, the results of a single model must be submitted to all benchmarks (indicated with an x below).

Stereo
Flow
Depth
Obj. Det.
Semantic
Instance
Panoptic

Important Dates

April 24, 2020 April 3, 2020 Training data and development kit released:
https://github.com/ozendelait/rvc_devkit/tree/release
July 1, 2020 RVC Submission system online
July 31, 2020 Submission deadline (6pm CEST)
August 07, 2020 Report deadline (6pm CEST)
August 28, 2020 Robust Vision Challenge 2020 Workshop at ECCV 2020 (Virtual Conference))



eXTReMe Tracker