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hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern RecognitionPreprint

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OmniMotionGPT: Animal Motion Generation with Limited Data

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Self-supervised AutoFlow

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DynaDog+T: A Parametric Animal Model for Synthetic Canine Image GenerationPreprint

Deane, J., Kearney, S., Kim, K. I., & Cosker, D. P. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.07330 · Cited by 8 · see citing works

DeepShapeKit: accurate 4D shape reconstruction of swimming fish

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BARC: Breed-Augmented Regression Using Classification for 3D Dog Reconstruction from Images

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Learning Fine-Grained Features for Pixel-wise Video Correspondences

Li, R., Zhou, S., & Liu, D. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00883 · Cited by 7 · see citing works

Neural Puppeteer: Keypoint-Based Neural Rendering of Dynamic Shapes

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DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension

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Shape of You: Precise 3D shape estimations for diverse body types

Sarkar, R., Dave, A., Medioni, G. G., & Biggs, B. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00357 · Cited by 6 · see citing works

Invertible Neural Skinning

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Animal Pose Estimation Based on 3D Priors

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Distilling Neural Fields for Real-Time Articulated Shape Reconstruction

Tan, J. S., Yang, G., & Ramanan, D. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00455 · Cited by 6 · see citing works

Coarse-to-fine Animal Pose and Shape EstimationPreprint

Li, C., & Lee, G. H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.08176 · Cited by 6 · see citing works

Generative Zoo

Niewiadomski, T., Yiannakidis, A., Cuevas-Velasquez, H., Sanyal, S., Black, M. J., Zuffi, S., & Kulits, P. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00795 · Cited by 5 · see citing works

KBody: Towards general, robust, and aligned monocular whole-body estimation

Zioulis, N., & O’Brien, J. F. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00661 · Cited by 5 · see citing works

ArMo: An Articulated Mesh Approach for Mouse 3D ReconstructionPreprint

Bohnslav, J. P., Osman, M. A. M., Jaggi, A., Soares, S., Weinreb, C., Datta, S. R., & Harvey, C. D. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.17.526719 · Cited by 5 · see citing works

RGBT-Dog: A Parametric Model and Pose Prior For Canine Body Analysis Data Creation

Deane, J., Kearney, S., Kim, K. I., & Cosker, D. P. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00595 · Cited by 3 · see citing works

DNA: Deformable Neural Articulations Network for Template-free Dynamic 3D Human Reconstruction from Monocular RGB-D Video

Vo-Ho, V.-K., Pham, T.-T., Yamazaki, K., Tran, M., & Le, N. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00375 · Cited by 3 · see citing works

RAPID AND AUTOMATED BODY MEASUREMENT OF CATTLE BASED ON STATISTICAL SHAPE MODEL

Bao, Y., Lu, H., Wu, J., Lei, J., Zhang, J., Luo, X., & Guo, H. (2023) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-x-1-w1-2023-541-2023 · Cited by 3 · see citing works

Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images

Li, C., Yang, Y., Weng, Z., Hernlund, E., Zuffi, S., & Kjellström, H. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0972-7_16 · Cited by 3 · see citing works

Markerless 3D kinematics and force estimation in cheetahs

da Silva, Z., Shield, S., Hudson, P. E., Wilson, A. M., Nicolls, F., & Patel, A. (2024) · Scientific Reports · doi:10.1038/s41598-024-60731-1 · Cited by 3 · see citing works

Giant Panda Video Image Sequence and Application in 3D Reconstruction

Hu, S., Liao, Z., Hou, R., & Chen, P. (2022) · Frontiers in Physics · doi:10.3389/fphy.2022.839582 · Cited by 2 · see citing works

Learning Part Segmentation from Synthetic Animals

Peng, J., He, J., Kaushik, P., Xiao, Z., Mu, J., & Yuille, A. (2024) · IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw60836.2024.00015 · Cited by 2 · see citing works

Unified 3D Mesh Recovery of Humans and Animals by Learning Animal Exercise

Kim, Y., Kim, J.-Y., Joo, K., & Oh, T.-H. (2021) · British Machine Vision Conference (BMVC) · doi:10.5244/c.35.268 · Cited by 2 · see citing works

AniMer+: Unified Pose and Shape Estimation Across Mammalia and Aves via Family-Aware Transformer

An, L., Lyu, J., Lin, L., Cheng, P., Liu, Y., & Tang, X. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3633828 · Cited by 1 · see citing works

Artificial Intelligence–Guided Behavioral Phenotyping in Epilepsy

Gschwind, T., & Soltész, I. (2024) · Oxford University Press eBooks · doi:10.1093/med/9780197549469.003.0060 · Cited by 1 · see citing works

Occluded Animal Shape and Pose Estimation from a Single Color Image

Xie, Y., Zhao, Y., Jiang, S., Hu, J., & Wang, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87358-5_34 · Cited by 1 · see citing works

Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive LearningPreprint

Bhattacharya, S., & Shahnawaz, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.08259 · Cited by 1 · see citing works

Discovering Relationships between Object Categories via Universal Canonical MapsPreprint

Neverova, N., Sanakoyeu, A., Labatut, P., Novotný, D., & Vedaldi, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.09758

Progress on Computational Ethology

Ren, W., Yu, S. P., & Zhang, Y. (2021) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2021-0213

Author response for "Argos: a toolkit for tracking multiple animals in complex visual environments"

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KBody: Balanced monocular whole-body estimation

Zioulis, N., & O’Brien, J. F. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00361

3D Shape Reconstruction of Semi-Transparent Worms

Ilett, T. P., Yuval, O., Ranner, T., Cohen, N., & Hogg, D. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.01209

A Horse with no Labels: Self-Supervised Horse Pose Estimation from Unlabelled Images and Synthetic Prior

Sosa, J., & Hogg, D. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00112

HitBack: Transformer With Hierarchical-Semantic Cross Attention and Background Contrast for Weakly Supervised Wildlife Semantic Segmentation

Xie, P., Zhuo, W., Wang, X., Deng, S., He, W., & Shen, L. (2026) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2026.3651016

Unsupervised and weakly supervised deep learning methods for computer vision and medical imaging

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RAT4D: Rig and Animate Objects without Surface Templates in 4D

Dabhi, M., Lucey, S., & Jeni, L. A. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00046

NeuralFur: Animal Fur Reconstruction from Multi-View Images

Sklyarova, V., Kabadayi, B., Yiannakidis, A., Becherini, G., Black, M. J., & Thies, J. (2026) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv69130.2026.00038

InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation

Peng, Y., Song, J.-T., Liao, C.-C., Kitani, K., Koike, H., & Wu, E. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-36839-3_24

PosePAL: Efficient Animal Pose Labeling Using Point Trackers

Pan, Z., Pan, B., Yang, G., Harley, A. W., & Guibas, L. (2026) · International Journal of Computer Vision · doi:10.1007/s11263-026-02976-z

Animal 3D reconstruction from videos

Ma, Y. (2023) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3-jast-3t96

ORMA: Optimization-based Monocular 4D Reconstruction of Articulated AnimalsPreprint

Hu, X., Palandra, F., Wu, S., Cremers, D., Marin, R., & Zuffi, S. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2609.37986

PRIMA: Boosting Animal Mesh Recovery with Taxonomic Priors and Adaptation-Driven Data BootstrappingPreprint

Yu, X., Wang, T., & Mathis, M. W. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2606.02366

Advances and Trends in the 3D Reconstruction of the Shape and Motion of AnimalsPreprint

Li, Z., Amrani, A., Rai, S., & Laga, H. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2508.16062 · Cited by 1 · see citing works

Retrieval, Recognition and Reconstruction of Quadruped Motions

Yasin, H., Zsoldos, R. R., & Weber, A. (2015)