CVPR 2023 accepted papers on Probabilistic and scientific modeling
29 of the 2,359 papers accepted at CVPR 2023 (1.2%) are on Probabilistic and scientific modeling, compared with 1.6% at CVPR 2022. They fall into 5 topics.
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Topics and papers
Molecules and proteins · 10 papers
- Neuron Structure Modeling for Generalizable Remote Physiological Measurement (64 citations)
- Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme Low-Light Photography (36 citations)
- Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction (35 citations)
- Don't Lie to Me! Robust and Efficient Explainability With Verified Perturbation Analysis (20 citations)
- Defining and Quantifying the Emergence of Sparse Concepts in DNNs (14 citations)
- Flexible-Cm GAN: Towards Precise 3D Dose Prediction in Radiotherapy (14 citations)
- Revisiting the Stack-Based Inverse Tone Mapping (8 citations)
- Tangentially Elongated Gaussian Belief Propagation for Event-Based Incremental Optical Flow Estimation (7 citations)
- FFF: Fragment-Guided Flexible Fitting for Building Complete Protein Structures (5 citations)
- Efficient Verification of Neural Networks Against LVM-Based Specifications (1 citation)
Uncertainty and Gaussian processes · 8 papers
- Robust Outlier Rejection for 3D Registration With Variational Bayes (58 citations)
- Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation (48 citations)
- Learning Analytical Posterior Probability for Human Mesh Recovery (24 citations)
- Robust and Scalable Gaussian Process Regression and Its Applications (20 citations)
- Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning (16 citations)
- Revisiting Rotation Averaging: Uncertainties and Robust Losses (12 citations)
- Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares (11 citations)
- Bayesian Posterior Approximation With Stochastic Ensembles (3 citations)
Variational and generative sampling · 6 papers
- Understanding Masked Autoencoders via Hierarchical Latent Variable Models (30 citations)
- RiDDLE: Reversible and Diversified De-Identification With Latent Encryptor (11 citations)
- Delving Into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling (8 citations)
- Learning Joint Latent Space EBM Prior Model for Multi-Layer Generator (7 citations)
- Understanding Deep Generative Models With Generalized Empirical Likelihoods (4 citations)
- A Unified Knowledge Distillation Framework for Deep Directed Graphical Models (1 citation)
Causal discovery · 4 papers
Dynamical systems · 1 paper
- Megahertz Light Steering Without Moving Parts (2 citations)