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

arXiv:2609.37986 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Benchmark — 11× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Robust Semantic Correspondence — 8× in this paper
• Accuracy — 6× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 6× in this paper
• European Conference on Computer Vision — 5× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Continuous Surface Embeddings — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Learned Perceptual Image Patch Similarity — 1× in this paper
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Root Mean Square Error — 1× in this paper
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• WildDepth: A Multimodal Dataset for 3D Wildlife Perception and Depth Estimation
• A Novel Dataset for Keypoint Detection of quadruped Animals from Images
• SAM 3D Animal: Promptable Animal 3D Reconstruction from Images in the Wild
• hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition
• ATRW: A Benchmark for Amur Tiger Re-identification in the Wild
• 4DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Video
• InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation
• DINOv3
• EmbodiedGen: Towards a Generative 3D World Engine for Embodied Intelligence
• DogMo: A Large-Scale Multi-View RGB-D Dataset for 4D Canine Motion Recovery
• LASR: Learning Articulated Shape Reconstruction from a Monocular Video
• AP-10K: A Benchmark for Animal Pose Estimation in the Wild
• PRIMA: Boosting Animal Mesh Recovery with Biological Priors and Test-Time Adaptation
• Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

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