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

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Computer Vision - ECCV 2024 Workshops : Milan, Italy, September 29-October 4, 2024, Proceedings, Part XIV (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 356 p.
  • 商品コード 9783031915772

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

.- AirLetters: An Open Video Dataset of Characters Drawn in the Air.
.- RegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation.
.- Generative Hierarchical Temporal Transformer for Hand Pose and Action Modeling.
.- Adaptive Multi-Modal Control of Digital Human Hand Synthesis Using a Region-Aware Cycle Loss.

.- Conditional Hand Image Generation using Latent Space Supervision in Random Variable Variational Autoencoders.
.- ChildPlay-Hand: A Dataset of Hand Manipulations in the Wild.
.- EMAG: Ego-motion Aware and Generalizable 2D Hand Forecasting from Egocentric Videos.
.- Disentangling Planning, Driving and Rendering for Photorealistic Avatar Agents.
.- RGMIM: Region-Guided Masked Image Modeling for Learning Meaningful Representations from X-Ray Images.
.- A Biologically-inspired Approach to Biomedical Image Segmentation.
.- Human-based Low-Level Visual Processing Neural Network for Image Segmentation.
.- Glia Cell Inspired Reinforcement Learning Agent for Neural Network Optimization.
.- Growing Deep Neural Network Considering with Similarity between Neurons.
.- Representation Learning in a Decomposed Encoder Design for Bio-inspired Hebbian Learning.
.- Reducing Catastrophic Forgetting in Online Class Incremental Learning Using Self-Distillation.
.- What makes a face look like a hat: Decoupling low-level and high-level visual properties with image triplets.
.- ScanDDM: Generalised Zero-Shot Neuro-Dynamical Modelling of GoalDirected Attention.
.- Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG.
.- Online Learning via Memory: Retrieval-Augmented Detector Adaptation.
.- AHMF: Adaptive Hybrid-Memory-Fusion Model for Driver Attention Prediction.
.- Accuracy Improvement of Cell Image Segmentation Using Feedback Former.
.- Variable resolution improves visual question answering under a limited pixel budget.
.- MOSAIC: Skeleton-based human motion recognition with compositional representations.
.- Adapting Large Language Model for Cross-Subject Semantic Decoding from Video-Stimulated fMRI.
.- A System 1 and System 2 Perspective on Continual Learning for Practical Implementation.
.- Connectivity-Inspired Network for Context-Aware Recognition.
.- Generalizability analysis of deep learning predictions of human brain responses to augmented and semantically novel visual stimuli.

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