Sparse-View Interpretable 3D Animal Behavior Representations for Neural Encoding and Decoding

arXiv:2609.36217 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-30

Terminology

• Point Clouds — 40× in this paper · explained in 2 episodes
• Embeddings — 35× in this paper · explained in 2 episodes
• Transformer — 30× in this paper · explained in 2 episodes
• Foundation Model — 8× in this paper · explained in 3 episodes
• Foundation Models — 8× in this paper · explained in 7 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Gaussian Splatting — 7× in this paper · explained in 4 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Video Depth Anything — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Clustering — 3× in this paper · explained in 2 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• International Brain Laboratory — 3× in this paper
• Latent Representation — 3× in this paper · explained in 2 episodes
• PEAK SIGNAL-TO-NOISE RATIO — 3× in this paper
• STRUCTURAL SIMILARITY INDEX MEASURE — 3× in this paper
• Visual Geometry Grounded Transformer — 3× in this paper
• Adaptation — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Principal Component Analysis — 2× in this paper
• Principal Component Analysis (PCA) — 2× in this paper · explained in 4 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Sparse-view Animal Behavior Latent Embeddings — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Pose Splatter: A 3D Gaussian Splatting Model for Quantifying Animal Pose and Appearance
• Depth Anything 3: Recovering the Visual Space from Any Views
• BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
• Sparse-View 3D Reconstruction: Recent Advances and Open Challenges

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