Computer Vision - ECCV 2024 Workshops : Milan, Italy, September 29-October 4, 2024, Proceedings, Part I (Lecture Notes in Computer Science)

Computer Vision - ECCV 2024 Workshops : Milan, Italy, September 29-October 4, 2024, Proceedings, Part I (Lecture Notes in Computer Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 418 p.
  • 商品コード 9783031915680

Full Description

The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29-October 4, 2024. 

These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of workshops and distribution of the workshop papers in the LNCS volumes can be found in the preface that is freely accessible online.

 

 

 

Contents

YCB-Ev 1.1: Event-vision dataset for 6DoF object pose estimation.- PCR-99: A Practical Method for Point Cloud Registration with 99 Percent Outliers.- Robust Single Rotation Averaging Revisited.- LanPose: Language-Instructed 6D Object Pose Estimation for Robotic Assembly.- SABER-6D: Shape Representation Based Implicit Object Pose Estimation.- FruitBin: a tunable large-scale dataset for advancing 6D pose estimation in fruit bin-picking automation.- Are Minimal Radial Distortion Solvers Necessary for Relative Pose Estimation?.- What's Wrong with the Absolute Trajectory Error?.- MPVO: Motion-Prior based Visual Odometry for PointGoal Navigation.- KRONC: Keypoint-based Robust Camera Optimization for 3D Car Reconstruction.- LVG-SfM: Learning-based View-Graph generation for robust on-the-fly SfM.- Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces.- PoTATO: A Dataset for Analyzing Polarimetric Traces of Afloat Trash Objects.- EVP: Enhanced Visual Perception using Inverse Multi-Attentive Feature Refinement and Regularized Image-Text Alignment.- Object Pose Estimation Using Implicit Representation For Transparent Objects.- TRICKY 2024 Challenge on Monocular Depth from Images of Specular and Transparent Surfaces.- ViscoNet: Bridging and Harmonizing Visual and Textual Conditioning for ControlNet.- Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models.- Fashion Attribute Extraction Under an Evolving Ontology.- Capturing and modeling real cloth deformations for virtual garment design.- MDiFF: Exploiting Multimodal Score-based Diffusion Models for New Fashion Product Performance Forecasting.- Deep Armocromia: A Novel Dataset for Face Seasonal Color Analysis and Classification.- DIVA: Deep Indic Virtual Apparel Try-On.- Garment Attribute Manipulation with Multi-level Attention.- Machine Learning-Driven Marketing Personas for the Luxury Fashion Market.

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