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Computer Vision ECCV 2024 Workshops: Milan, Italy, September 29October 4, 202 [Paperback]

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  • Category: Books (Computers)
  • ISBN-10:  3031915771
  • ISBN-10:  3031915771
  • ISBN-13:  9783031915772
  • ISBN-13:  9783031915772
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  390
  • Pages:  390
  • Binding:  Paperback
  • Binding:  Paperback
  • SKU:  3031915771-11-SPRI
  • SKU:  3031915771-11-SPRI
  • Item ID: 106926582
  • List Price: $99.99
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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.

 

 

 

.- 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 Learninl#w

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