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Computer Vision – ECCV 2022 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXIII / edited by Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giov...
Published 2022Table of Contents: “…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 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.…”
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