Computer Vision – ECCV 2022 : 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXVIII / edited by Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner.

Format:

Book

Contributor:

Avidan, Shai, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13688

Language:

English

Subjects (All):

Computer vision.

Computer Vision.

Local Subjects:

Computer Vision.

Physical Description:

1 online resource (806 pages)

Edition:

1st ed. 2022.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2022.

Summary:

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:

Salient Object Detection for Point Clouds

Learning Semantic Segmentation from Multiple Datasets with Label Shifts

Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination

Towards Open-Vocabulary Scene Graph Generation with Prompt-Based Finetuning

Variance-Aware Weight Initialization for Point Convolutional Neural Networks

Break and Make: Interactive Structural Understanding Using LEGO Bricks

Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation

3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching

Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions

MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud

Scene Text Recognition with Permuted Autoregressive Sequence Models

When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition

Detecting Tampered Scene Text in the Wild

Optimal Boxes: Boosting End-to-End Scene Text Recognition by Adjusting Annotated Bounding Boxes via Reinforcement Learning

GLASS: Global to Local Attention for Scene-Text Spotting

COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts

Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detection and Spotting

Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition

Levenshtein OCR

Multi-Granularity Prediction for Scene Text Recognition

Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting

Contextual Text Block Detection towards Scene Text Understanding

CoMER: Modeling Coverage for Transformer-Based Handwritten Mathematical Expression Recognition

Don’t Forget Me: Accurate Background Recovery for Text Removal via Modeling Local-Global Context

TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers

Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features

SGBANet: Semantic GAN and Balanced Attention Network for Arbitrarily Oriented Scene Text Recognition

Pure Transformer with Integrated Experts for Scene Text Recognition

OCR-Free Document Understanding Transformer

CAR: Class-Aware Regularizations for Semantic Segmentation

Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation

SeqFormer: Sequential Transformer for Video Instance Segmentation

Saliency Hierarchy Modeling via Generative Kernels for Salient Object Detection

In Defense of Online Models for Video Instance Segmentation

Active Pointly-Supervised Instance Segmentation

A Transformer-Based Decoder for Semantic Segmentation with Multi-level Context Mining

XMem: Long-Term Video Object Segmentation with an Atkinson- Shiffrin Memory Model

Self-Distillation for Robust LiDAR Semantic Segmentation in Autonomous Driving

2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds

Extract Free Dense Labels from CLIP

3D Compositional Zero-Shot Learning with DeCompositional Consensus

Video Mask Transfiner for High-Quality Video Instance Segmentation.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Avidan, Shai Computer Vision - ECCV 2022

ISBN:

9783031198151

3031198158

OCLC:

1348480892