2nd Causality in Vision (CiV) Call for Papers


2nd Causality in Vision (CiV)



2022 NICO Common Context Generalization Challenge


In conjunction with the 17th European Conference on Computer Vision (ECCV 2022)


Tel-Aviv, Israel, Oct. 23-27 2022.


The goal of this workshop is to provide a comprehensive yet accessible
overview of existing causality research and to help CV researchers to
know why and how to apply causality in their own work. We aim to
invite speakers from this area to present their latest works and
propose new challenges.


We invite submissions of papers related to the applications/theories
of causality in computer vision, including but not limited to:

* Causal discovery for high-dimensional visual data

* Causal inference for fair and explainable deep models

* Causal inference for robust visual models

* Causality combined with unsupervised, supervised, and reinforcement learning

* Learning visual causal generative mechanisms

* Structural causal models for heterogeneous and multimodal data

* Novel models combined vision and causality

* Visual causality data collection, benchmarking, and performance evaluation


Workshop submissions are open! Visit the website:



Important dates:

- Submission deadline: July 22, 2022 (11:59pm Pacific Standard Time).

- Notification to authors: April 17, 2022 (11:59pm Pacific Standard Time).

- Camera-ready deadline: August 22, 2022 (11:59pm Pacific Standard Time).

- Workshop: October 23 or 24, 2022




The goal of NICO Challenge is to facilitate the OOD
(Out-of-Distribution) generalization in visual recognition through
promoting the research on the intrinsic learning mechanisms with
native invariance and generalization ability. The training data is a
mixture of several observed contexts while the test data is composed
of unseen contexts. Participants are tasked with developing reliable
algorithms across different contexts (domains) to improve the
generalization ability of models.

The NICO Challenge is an image recognition competition containing two
main tracks: 1) common context generalization (Domain Generalization,
DG) track; 2) hybrid context generalization track. The difference of
these two tracks is whether the context used in training data for all
the categories are aligned (e.g. common contexts) and the availability
of context (domain) labels. Same as the classic DG setting, all the
contexts are common contexts that are aligned for all categories in
both training and test data in the common context generalization
track. Nevertheless, both common and unique contexts are used for the
hybrid context generalization track where the contexts varies across
different categories. Context labels are available for the common
context generalization track while unavailable for the hybrid context
generalization track.

To participate, please register on host-website [Codalab] and create a
team for the challenge.

Track 1: Common Context Generalization


Track 2: Hybrid Context Generalization



Important dates:

- 2022-04-18 Releasing the NICO++ dataset. (See the DATASET)

- 2022-04-20 Start Date of Phase 1.

- 2022-07-10 Deadline of Phase 1. This is the last day for team
registration and result submission.

- 2022-07-12 Notification of winner teams in Phase 1. Start Date of
Phase 2.

- 2022-07-30 Deadline of Phase 2. This is the last day for Top 10
teams to submit the model.

- 2022-08-10 Notification of Final Winners.

All deadlines are at 23:59 AoE on the corresponding day unless otherwise noted.


Workshop Organizers:

Yulei Niu, Columbia University, New York, United States

Hanwang Zhang, Nanyang Technological University, Singapore

Peng Cui, Tsinghua University, Beijing, China

Song-Chun Zhu, Peking University, Beijing, China

Qianru Sun, Singapore Management University, Singapore

Mike Zheng Shou, National University of Singapore, Singapore


Challenge Organizers:

Peng Cui, Tsinghua University, Beijing, China

Hanwang Zhang, Nanyang Technological University, Singapore

David Lopez-Paz, Meta AI Paris, France