Computer Vision – ECCV 2022 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXIII

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 forGeneralizable 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 lq-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.