CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling Call for Papers

Call for Paper
CVPR 2021 Workshop on 
CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling 

Submission deadline: 11:59 pm, Apri 30, 2021 (Pacific Time)

Many biological organisms have evolved to exhibit diverse behaviors,
and understanding these behaviors is a fundamental goal of multiple
disciplines including neuroscience, biology, animal husbandry,
ecology, and animal conservation. These analyses require objective,
repeatable, and scalable measurements of animal behaviors that are not
possible with existing methodologies that leverage manual encoding
from animal experts and specialists. Computer vision is having an
impact across multiple disciplines by providing new tools for the
detection, tracking, and analysis of animal behavior. This workshop
brings together experts across fields to stimulate this new field of
computer-vision-based animal behavioral understanding.

We solicit exciting non-archival papers on the related topics of
CV4Animals. The selected papers will be presented in the workshop as a
poster (will not be published in proceedings). There are two tracks.

Track 1 (unpublished work): Paper must follow the CVPR format, and be
limited to 4 pages plus references. Papers will be reviewed in
accordance with double blind policy, based on relevance, significance,
and novelty.

Track 2 (published work): We look for papers already published at a
peer-reviewed venue. Full paper can be submitted without a

Our goal is to increase visibility and unique problems that arise when
using computer vision to understand animal behavior. We welcome any
papers around topics of:

- Animal Re-identification

- 3D Animal Reconstruction

- Animal Tracking and Modeling

- Animal Behavioral Analysis

- Animal Datasets

- CV Applications in Neuroscience, Biology, Animal Husbandry, Ecology, and Animal Conservation

Submission deadline: 11:59 pm, Apri 30, 2021 (Pacific Time)

Notification of selection: May 21, 2021

Submission: CMT link (Track 1) and 

Google form (Track 2)