ArticleeLife2025
Anti-drift pose tracker (ADPT), a transformer-based network for robust animal pose estimation cross-species.
Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Article
- Cracking the Valence Code: Patterned Facial Kinematics and Neural Signatures of Emotional Expressions in Mice.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- A Deep Learning Framework for Multi-Object Tracking in Space Animal Behavior Studies.Animals : an open access journal from MDPI · 2025Article
- Anti-drift pose tracker (ADPT), a transformer-based network for robust animal pose estimation cross-species.eLife · 2025Article
- A Study of Spontaneous Self-Injurious Behavior and Neuroimaging in Rhesus Macaques.Research (Washington, D.C.) · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Deep learning-based methods have advanced animal pose estimation, enhancing accuracy, and efficiency in quantifying animal behavior. However, these methods frequently experience tracking drift, where noise-induced jumps in body point estimates compromise reliability. Here, we present the anti-drift pose tracker (ADPT), a transformer-based tool that mitigates tracking drift in behavioral analysis. Extensive experiments across cross-species datasets-including proprietary mouse and monkey recordings and public
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.