Full Description
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23-27, 2022.
The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Contents
Lane Detection Transformer Based on Multi-Frame Horizontal andVertical Attention and Visual Transformer Module.- ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection.- PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map.- Master of All: Simultaneous Generalization of Urban-Scene Segmentation to All Adverse Weather Conditions.- LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds.- Visual Cross-View Metric Localization with Dense Uncertainty Estimates.- V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer.- DevNet: Self-Supervised Monocular Depth Learning via Density Volume Construction.- Action-Based Contrastive Learning for Trajectory Prediction.- Radatron: Accurate Detection Using Multi-Resolution Cascaded MIMO Radar.- LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection.- Efficient Point Cloud Segmentation with Geometry-Aware Sparse Networks.- FH-Net: A Fast Hierarchical Network for Scene Flow Estimation on Real-World Point Clouds.- SpatialDETR: Robust Scalable Transformer-Based 3D Object Detection from Multi-View Camera Images with Global Cross-Sensor Attention.- Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes.- Rethinking Closed-Loop Training for Autonomous Driving.- SLiDE: Self-Supervised LiDAR De-Snowing through Reconstruction Difficulty.- Generative Meta-Adversarial Network for Unseen Object Navigation.- Object Manipulation via Visual Target Localization.- MoDA: Map Style Transfer for Self-Supervised Domain Adaptation of Embodied Agents.- Housekeep: Tidying Virtual Households Using Commonsense Reasoning.- Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects.- Resolving Copycat Problems in Visual Imitation Learning via Residual Action Prediction.- OPD: Single-View 3D Openable Part Detection.- AirDet: Few-Shot Detection without Fine-Tuning for Autonomous Exploration.- TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instance.- StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning.- TIDEE: Tidying Up Novel Rooms Using Visuo-Semantic Commonsense Priors.- Learning Efficient Multi-agent Cooperative Visual Exploration.- Zero-Shot Category-Level Object Pose Estimation.- Sim-to-Real 6D Object Pose Estimation via Iterative Self-Training for Robotic Bin Picking.- Active Audio-Visual Separation of Dynamic Sound Sources.- DexMV: Imitation Learning for Dexterous Manipulation from Human Videos.- Sim-2-Sim Transfer for Vision-and-Language Navigation in Continuous Environments.- Style-Agnostic Reinforcement Learning.- Self-Supervised Interactive Object Segmentation through a Singulation-and-Grasping Approach.- Learning from Unlabeled 3D Environmentsfor Vision-and-Language Navigation.- BodySLAM: Joint Camera Localisation, Mapping, and Human Motion Tracking.- FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion.- Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning.- Video Dialog As Conversation about Objects Living in Space-Time.
