Computer Vision – ECCV 2024 Workshops Milan, Italy, September 29–October 4, 2024, Proceedings, Part XI /

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...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros Autores: Del Bue, Alessio (Editor), Canton, Cristian (Editor), Pont-Tuset, Jordi (Editor), Tommasi, Tatiana (Editor)
Formato: Recurso Electrónico livro electrónico
Idioma:inglês
Publicado em: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edição:1st ed. 2025.
Colecção:Lecture Notes in Computer Science, 15633
Assuntos:
Acesso em linha:https://doi.org/10.1007/978-3-031-91979-4
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
Sumário:
  • DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector LoRA of the Foundation Model
  • LocalMamba: Visual State Space Model with Windowed Selective Scan
  • Compositional Text-to-Image Generation with Feedforward Layout Generation
  • PackMamba:Efficient Processing of Variable-Length Sequences in Mamba training
  • Down-Sampling Inter-Layer Adapter for Parameter and Computation Efficient Ultra-Fine-Grained Image Recognition
  • Memory-Efficient Vision Transformers: An Activation-Aware Mixed-Rank Compression Strategy
  • LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models
  • Improving Hyperparameter Optimization with Checkpointed Model Weights
  • MagicDec: Breaking the Latency-Throughput Tradeoff for Long Contexts with Speculative Decoding
  • Mixed Non-linear Quantization for Vision Transformers
  • CycleBNN: Cyclic Precision Training in Binary Neural Networks
  • DailyMAE: Towards Pretraining Masked Autoencoders in One Day
  • EPTQ: Enhanced Post-Training Quantization via Hessian-guided Network-wise Optimization
  • Generalized SAM: Efficient Fine-Tuning of SAM for Variable Input Image Sizes
  • LightAvatar: Efficient Head Avatar as Dynamic Neural Light Field
  • Giving each task what it needs - leveraging structured sparsity for tailored multi-task learning
  • ERF-NAS: Efficient Receptive Field-based Zero-Shot NAS for Object Detection
  • CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge
  • Memory-Optimized Once-For-All network
  • Famba-V: Fast Vision Mamba with Cross-Layer Token Fusion
  • Latent Distillation for Continual Object Detection at the Edge
  • MCUBench: A Benchmark of Tiny Object Detectors on MCUs
  • Optimizing Resource Consumption in Diffusion Models through Hallucination Early Detection.