Animal Pose Estimation
27 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
Latest papers
Domain adaptive pose estimation via multi-level alignment
sunshinglight/DAML_PoseEstimation
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Specifically, we first utilize image style transer to ensure that images from the source and target domains have a similar distribution.
APTv2: Benchmarking Animal Pose Estimation and Tracking with a Large-scale Dataset and Beyond
Animal Pose Estimation and Tracking (APT) is a critical task in detecting and monitoring the keypoints of animals across a series of video frames, which is essential for understanding animal behavior.
Pose Anything: A Graph-Based Approach for Category-Agnostic Pose Estimation
This approach not only enables object pose generation based on arbitrary keypoint definitions but also significantly reduces the associated costs, paving the way for versatile and adaptable pose estimation applications.
Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
This paper identifies the importance of being geometry-aware for semantic correspondence and reveals a limitation of the features of current foundation models under simple post-processing.
UniPose: Detecting Any Keypoints
This work proposes a unified framework called UniPose to detect keypoints of any articulated (e. g., human and animal), rigid, and soft objects via visual or textual prompts for fine-grained vision understanding and manipulation.
Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
amathislab/BUCTD
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Frequent interactions between individuals are a fundamental challenge for pose estimation algorithms.
SPAC-Net: Synthetic Pose-aware Animal ControlNet for Enhanced Pose Estimation
ostadabbas/SPAC-Net-Synthetic-Pose-aware-Animal-ControlNet
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Our work demonstrates the potential for synthetic data to overcome the challenge of limited annotated data in animal pose estimation.
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.
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.
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.
