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

Format:

Book

Author/Creator:

Avidan, Shai, author.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13689

Language:

English

Subjects (All):

Computer vision.

Education--Data processing.

Education.

Database management.

Social sciences--Data processing.

Social sciences.

Pattern recognition systems.

Machine learning.

Computer Vision.

Computers and Education.

Database Management.

Computer Application in Social and Behavioral Sciences.

Automated Pattern Recognition.

Machine Learning.

Local Subjects:

Computer Vision.

Computers and Education.

Database Management.

Computer Application in Social and Behavioral Sciences.

Automated Pattern Recognition.

Machine Learning.

Physical Description:

1 online resource (812 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:

Box-Supervised Instance Segmentation with Level Set Evolution

Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding

Adaptive Agent Transformer for Few-Shot Segmentation

Waymo Open Dataset: Panoramic Video Panoptic Segmentation

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-Shot Interactions

Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation

Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications

Perceptual Artifacts Localization for Inpainting

2D Amodal Instance Segmentation Guided by 3D Shape Prior

Data Efficient 3D Learner via Knowledge Transferred from 2D Model

Adaptive Spatial-BCE Loss for Weakly Supervised Semantic Segmentation

Dense Gaussian Processes for Few-Shot Segmentation

3D Instances as 1D Kernels

TransMatting: Enhancing Transparent Objects Matting with Transformers

MVSalNet:Multi-View Augmentation for RGB-D Salient Object Detection

k-Means Mask Transformer

SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness

Adversarial Erasing Framework via Triplet with Gated Pyramid Pooling Layer for Weakly Supervised Semantic Segmentation

Continual Semantic Segmentation via Structure Preserving and Projected Feature Alignment

Interclass Prototype Relation for Few-Shot Segmentation

Slim Scissors: Segmenting Thin Object from Synthetic Background

Abstracting Sketches through Simple Primitives

Multi-Scale and Cross-Scale Contrastive Learning for Semantic Segmentation

One-Trimap Video Matting

D2ADA: Dynamic Density-Aware Active Domain Adaptation for Semantic Segmentation

Learning Quality-Aware Dynamic Memory for Video Object Segmentation

Learning Implicit Feature Alignment Function for Semantic Segmentation

Quantum Motion Segmentation

Instance As Identity: A Generic Online Paradigm for Video Instance Segmentation

Laplacian Mesh Transformer: Dual Attention and Topology Aware Network for 3D Mesh Classification and Segmentation

Geodesic-Former: A Geodesic-Guided Few-Shot 3D Point Cloud Instance Segmenter

Union-Set Multi-source Model Adaptation for Semantic Segmentation

Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions

BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation

SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection

Global Spectral Filter Memory Network for Video Object Segmentation

Video Instance Segmentation via Multi-Scale Spatio-Temporal Split Attention Transformer

RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation

Learning Topological Interactions for Multi-Class Medical Image Segmentation

Unsupervised Segmentation in Real-World Images via Spelke Object Inference

A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-Language Model.

Other Format:

Print version: Avidan, Shai Computer Vision - ECCV 2022

ISBN:

9783031198182

3031198182