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avidan shai (curatore); brostow gabriel (curatore); cissé moustapha (curatore); farinella giovanni maria (curatore); hassner tal (curatore) - computer vision – eccv 2022

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

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 11/2022
Edizione: 1st ed. 2022





Trama

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.





Sommario

DFNet: Enhance Absolute Pose Regression with Direct Feature Matching.- Cornerformer: Purifying Instances for Corner-Based Detectors.- Robust Object Detection with Inaccurate Bounding Boxes.- Efficient Decoder-Free Object Detection with Transformers.- Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection.- ReAct: Temporal Action Detection with Relational Queries.- Towards Accurate Active Camera Localization.- Camera Pose Auto-Encoders for Improving Pose Regression.- Improving the Intra-Class Long-Tail in 3D Detection via Rare Example Mining.- Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization.- UC-OWOD: Unknown-Classified Open World Object Detection.- RayTran: 3D Pose Estimation and Shape Reconstruction of Multiple
Objects from Videos with Ray-Traced Transformers.- GTCaR: Graph Transformer for Camera Re-Localization.- 3D Object Detection with aSelf-Supervised Lidar Scene Flow Backbone.- Open Vocabulary Object Detection with Pseudo Bounding-Box Labels.- Few-Shot Object Detection by Knowledge Distillation Using Bag-of-Visual-Words Representations.- SALISA: Saliency-Based Input Sampling for Efficient Video Object
Detection.- ECO-TR: Efficient Correspondences Finding via Coarse-to-Fine
Refinement.- Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by
Radial Keypoint Voting.- Long-Tailed Instance Segmentation Using Gumbel Optimized Loss.- DetMatch: Two Teachers Are Better than One for Joint 2D and 3D
Semi-Supervised Object Detection.- ObjectBox: From Centers to Boxes for Anchor-Free Object Detection.- Is Geometry Enough for Matching in Visual Localization?.- SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds.- PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry.- GLAMD:Global and Local Attention Mask Distillation for Object Detectors.- FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection.- Video Anomaly Detection by Solving Decoupled Spatio-Temporal
Jigsaw Puzzles.- Class-Agnostic Object Detection with Multi-modal Transformer.- Enhancing Multi-modal Features Using Local Self-Attention for 3D
Object Detection.- Object Detection As Probabilistic Set Prediction.- Weakly-Supervised Temporal Action Detection for Fine-Grained Videos with Hierarchical Atomic Actions.- Neural Correspondence Field for Object Pose Estimation.- On Label Granularity and Object Localization.- OIMNet++: Prototypical Normalization and Localization-Aware
Learning for Person Search.- Out-of-Distribution Identification: Let Detector Tell Which I Am Not Sure.- Learning with Free Object Segments for Long-Tailed Instance
Segmentation.- Autoregressive Uncertainty Modelingfor 3D Bounding Box Prediction.- 3D Random Occlusion and Multi-layer Projection for Deep Multi-Camera Pedestrian Localization.- A Simple Single-Scale Vision Transformer for Object Detection and
Instance Segmentation.- Simple Open-Vocabulary Object Detection with Vision Transformers










Altre Informazioni

ISBN:

9783031200793

Condizione: Nuovo
Collana: Lecture Notes in Computer Science
Dimensioni: 235 x 155 mm
Formato: Brossura
Illustration Notes:LVII, 759 p. 226 illus., 221 illus. in color.
Pagine Arabe: 759
Pagine Romane: lvii


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