Animal Pose Estimation
25 papers with code • 8 benchmarks • 17 datasets
Animal pose estimation is the task of identifying the pose of an animal.
( Image credit: Using DeepLabCut for 3D markerless pose estimation across species and behaviors )
Benchmarks
These leaderboards are used to track progress in Animal Pose Estimation
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Libraries
Use these libraries to find Animal Pose Estimation models and implementationsDatasets
AP-10K
Animal-Pose Dataset
Animal Kingdom
StanfordExtra
ATRW
Horse-10
AwA Pose
TriMouse-161
MBW - Zoo Dataset
Most implemented papers
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild
Animals are capable of extreme agility, yet understanding their complex dynamics, which have ecological, biomechanical and evolutionary implications, remains challenging.
From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
chaneyddtt/UDA-Animal-Pose
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CVPR 2021
Existing works circumvent this problem with pseudo labels generated from data of other easily accessible domains such as synthetic data.
T-LEAP: Occlusion-robust pose estimation of walking cows using temporal information
hrussel/t-leap
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On occluded data, our temporal approach outperformed the static one by up to 32. 9%, suggesting that using temporal data was beneficial for pose estimation in environments prone to occlusions, such as dairy farms.
A Unified Framework for Domain Adaptive Pose Estimation
visionlearninggroup/uda_poseestimation
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In this paper, we investigate the problem of domain adaptive 2D pose estimation that transfers knowledge learned on a synthetic source domain to a target domain without supervision.
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior Understanding
SUTDCV/Animal-Kingdom
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CVPR 2022
More specifically, our dataset contains 50 hours of annotated videos to localize relevant animal behavior segments in long videos for the video grounding task, 30K video sequences for the fine-grained multi-label action recognition task, and 33K frames for the pose estimation task, which correspond to a diverse range of animals with 850 species across 6 major animal classes.
CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal Pose
xuzhang1199/clamp
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CVPR 2023
Motivated by the progress of visual-language research, we propose that pre-trained language models (e. g., CLIP) can facilitate animal pose estimation by providing rich prior knowledge for describing animal keypoints in text.
Prior-Aware Synthetic Data to the Rescue: Animal Pose Estimation with Very Limited Real Data
ostadabbas/prior-aware-synthetic-data-generation-pasyn-
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Here, we present a very data efficient strategy targeted for pose estimation in quadrupeds that requires only a small amount of real images from the target animal.
ViTPose++: Vision Transformer for Generic Body Pose Estimation
In this paper, we show the surprisingly good properties of plain vision transformers for body pose estimation from various aspects, namely simplicity in model structure, scalability in model size, flexibility in training paradigm, and transferability of knowledge between models, through a simple baseline model dubbed ViTPose.
3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture
Recent advances in machine learning and computer vision are revolutionizing the field of animal behavior by enabling researchers to track the poses and locations of freely moving animals without any marker attachment.
ScarceNet: Animal Pose Estimation with Scarce Annotations
chaneyddtt/scarcenet
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CVPR 2023
To this end, we propose the ScarceNet, a pseudo label-based approach to generate artificial labels for the unlabeled images.
