{"total":42,"rows":[{"id":"2303.05512","title":"PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification","created":"2023-03-09","cited_by_count":154,"area":null},{"id":"2102.13156","title":"Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling","created":"2021-02-25","cited_by_count":59,"area":null},{"id":"2406.14927","title":"GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation","created":"2024-06-21","cited_by_count":49,"area":null},{"id":"2201.10085","title":"Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately","created":"2022-01-25","cited_by_count":47,"area":null},{"id":"2107.01272","title":"Physics-Guided Deep Learning for Dynamical Systems: A Survey","created":"2021-07-02","cited_by_count":44,"area":null},{"id":"2509.21309","title":"NewtonGen: Physics-Consistent and Controllable Text-to-Video Generation via Neural Newtonian Dynamics","created":"2025-09-25","cited_by_count":41,"area":null},{"id":"2210.15664","title":"State of the Art in Dense Monocular Non-Rigid 3D Reconstruction","created":"2022-10-27","cited_by_count":30,"area":null},{"id":"2501.10928","title":"Generative Physical AI in Vision: A Survey","created":"2025-01-19","cited_by_count":24,"area":null},{"id":"2203.11938","title":"{\\phi}-SfT: Shape-from-Template with a Physics-Based Deformation Model","created":"2022-03-22","cited_by_count":23,"area":null},{"id":"2311.02007","title":"Towards Unsupervised Object Detection From LiDAR Point Clouds","created":"2023-11-03","cited_by_count":23,"area":null},{"id":"2202.06481","title":"A Survey on Machine Learning Approaches for Modelling Intuitive Physics","created":"2022-02-14","cited_by_count":20,"area":null},{"id":"2204.14030","title":"Neural Implicit Representations for Physical Parameter Inference from a Single Video","created":"2022-04-29","cited_by_count":19,"area":null},{"id":"2406.04155","title":"Improving Physics-Augmented Continuum Neural Radiance Field-Based Geometry-Agnostic System Identification with Lagrangian Particle Optimization","created":"2024-06-06","cited_by_count":16,"area":null},{"id":"2107.08881","title":"Reasoning-Modulated Representations","created":"2021-07-19","cited_by_count":13,"area":null},{"id":"2410.01376","title":"Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems","created":"2024-10-02","cited_by_count":13,"area":null},{"id":"2111.05393","title":"Object-Centric Representation Learning with Generative Spatial-Temporal Factorization","created":"2021-11-09","cited_by_count":10,"area":null},{"id":"2402.05970","title":"Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts","created":"2024-02-06","cited_by_count":9,"area":null},{"id":"2304.03492","title":"ClothCombo: Modeling Inter-Cloth Interaction for Draping Multi-Layered Clothes","created":"2023-04-07","cited_by_count":7,"area":null},{"id":"2304.06704","title":"How Will It Drape Like? Capturing Fabric Mechanics from Depth Images","created":"2023-04-13","cited_by_count":6,"area":null},{"id":"2109.05928","title":"Vision-based system identification and 3D keypoint discovery using dynamics constraints","created":"2021-09-13","cited_by_count":5,"area":null},{"id":"2512.03350","title":"SeeU: Seeing the Unseen World via 4D Dynamics-aware Generation","created":"2025-12-03","cited_by_count":5,"area":null},{"id":"2603.16432","title":"IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video","created":"2026-03-17","cited_by_count":4,"area":null},{"id":"2503.19976","title":"Thin-Shell-SfT: Fine-Grained Monocular Non-rigid 3D Surface Tracking with Neural Deformation Fields","created":"2025-03-25","cited_by_count":3,"area":null},{"id":"2205.01314","title":"Distilling Governing Laws and Source Input for Dynamical Systems from Videos","created":"2022-05-03","cited_by_count":2,"area":null},{"id":"2601.00504","title":"MotionPhysics: Learnable Motion Distillation for Text-Guided Simulation","created":"2026-01-01","cited_by_count":2,"area":null},{"id":"2604.09527","title":"Envisioning the Future, One Step at a Time","created":"2026-04-10","cited_by_count":2,"area":null},{"id":"2106.04776","title":"Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos","created":"2021-06-09","cited_by_count":1,"area":null},{"id":"2111.05514","title":"Discovering Latent Representations of Relations for Interacting Systems","created":"2021-11-10","cited_by_count":1,"area":null},{"id":"2406.18220","title":"Guiding Video Prediction with Explicit Procedural Knowledge","created":"2024-06-26","cited_by_count":1,"area":null},{"id":"2110.08239","title":"Learn Proportional Derivative Controllable Latent Space from Pixels","created":"2021-10-15","cited_by_count":0,"area":null},{"id":"2206.11030","title":"KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images","created":"2022-06-22","cited_by_count":0,"area":null},{"id":"2403.08194","title":"Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2404.17865","title":"Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target","created":"2024-04-27","cited_by_count":0,"area":null},{"id":"2407.09537","title":"ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge","created":"2024-06-26","cited_by_count":0,"area":null},{"id":"2507.22699","title":"Image-Guided Shape-from-Template Using Mesh Inextensibility Constraints","created":"2025-07-30","cited_by_count":0,"area":null},{"id":"2508.06335","title":"ViPro-2: Unsupervised State Estimation via Integrated Dynamics for Guiding Video Prediction","created":"2025-08-08","cited_by_count":0,"area":null},{"id":"2512.15493","title":"Soft Geometric Inductive Bias for Object Centric Dynamics","created":"2025-12-17","cited_by_count":0,"area":null},{"id":"2512.24826","title":"Video and Language Alignment in 2D Systems for 3D Multi-object Scenes with Multi-Information Derivative-Free Control","created":"2025-12-31","cited_by_count":0,"area":null},{"id":"2604.02031","title":"Rare-Aware Autoencoding: Reconstructing Spatially Imbalanced Data","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2605.22597","title":"MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2605.24047","title":"EMMA: Extracting Multiple physical parameters from Multimodal Data","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2607.06871","title":"Geometric Collapse: When Vision Models Fail to Verify Physical Causality","created":"2026-07-08","cited_by_count":0,"area":null}],"next_cursor":null}