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Accelerating Score-Based Generative Models with Preconditioned Diffusion Sampling
Learning to Generate Realistic LiDAR Point Clouds
RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds
Diverse Image Inpainting with Normalizing Flow
Improved Masked Image Generation with Token-Critic
TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation
Exploring Gradient-Based Multi-directional Controls in GANs
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition
Neural Scene Decoration from a Single Photograph
Outpainting by Queries
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
ChunkyGAN: Real Image Inversion via Segments
GAN Cocktail: Mixing GANs without Dataset Access
Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering
Controllable Shadow Generation Using Pixel Height Maps
Learning Where to Look Generative NAS Is Surprisingly Efficient
Subspace Diffusion Generative Models
DuelGAN: A Duel between Two Discriminators Stabilizes the GAN Training
MINER: Multiscale Implicit Neural Representation
An Embedded Feature Whitening Approach to Deep Neural Network Optimization
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
Self-Supervised Learning of Visual Graph Matching
Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models
QISTA-ImageNet: A Deep Compressive Image Sensing Framework Solving q-Norm Optimization Problem
R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning
Domain Generalization by Mutual-Information Regularization with Pre-trained Models
Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine Learning
Neural-Sim: Learning to Generate Training Data with NeRF
Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning
Learned Variational Video Color Propagation
Continual Variational Autoencoder Learning via Online Cooperative Memorization
Learning to Learn with Smooth Regularization
Incremental Task Learning with Incremental Rank Updates
Batch-Efficient EigenDecomposition for Small and Medium Matrices
Ensemble Learning Priors Driven Deep Unfolding for Scalable Video Snapshot Compressive Imaging
Approximate Discrete Optimal Transport Plan with Auxiliary Measure Method
A Comparative Study of Graph Matching Algorithms in Computer Vision
Improving Generalization in Federated Learning by Seeking Flat Minima
Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not
Transfer without Forgetting
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation
Tackling Long-Tailed Category Distribution under Domain Shifts
Doubly-Fused ViT: Fuse Information from Vision Transformer Doubly with Local Representation.
Learning to Generate Realistic LiDAR Point Clouds
RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds
Diverse Image Inpainting with Normalizing Flow
Improved Masked Image Generation with Token-Critic
TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation
Exploring Gradient-Based Multi-directional Controls in GANs
Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene Decomposition
Neural Scene Decoration from a Single Photograph
Outpainting by Queries
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
ChunkyGAN: Real Image Inversion via Segments
GAN Cocktail: Mixing GANs without Dataset Access
Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering
Controllable Shadow Generation Using Pixel Height Maps
Learning Where to Look Generative NAS Is Surprisingly Efficient
Subspace Diffusion Generative Models
DuelGAN: A Duel between Two Discriminators Stabilizes the GAN Training
MINER: Multiscale Implicit Neural Representation
An Embedded Feature Whitening Approach to Deep Neural Network Optimization
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
Self-Supervised Learning of Visual Graph Matching
Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models
QISTA-ImageNet: A Deep Compressive Image Sensing Framework Solving q-Norm Optimization Problem
R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning
Domain Generalization by Mutual-Information Regularization with Pre-trained Models
Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine Learning
Neural-Sim: Learning to Generate Training Data with NeRF
Bayesian Optimization with Clustering and Rollback for CNN Auto Pruning
Learned Variational Video Color Propagation
Continual Variational Autoencoder Learning via Online Cooperative Memorization
Learning to Learn with Smooth Regularization
Incremental Task Learning with Incremental Rank Updates
Batch-Efficient EigenDecomposition for Small and Medium Matrices
Ensemble Learning Priors Driven Deep Unfolding for Scalable Video Snapshot Compressive Imaging
Approximate Discrete Optimal Transport Plan with Auxiliary Measure Method
A Comparative Study of Graph Matching Algorithms in Computer Vision
Improving Generalization in Federated Learning by Seeking Flat Minima
Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or Not
Transfer without Forgetting
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation
Tackling Long-Tailed Category Distribution under Domain Shifts
Doubly-Fused ViT: Fuse Information from Vision Transformer Doubly with Local Representation.