| Record Type: |
Electronic resources
: Monograph/item
|
| Title/Author: |
Computer vision - ECCV 2024/ edited by Aleš Leonardis ... [et al.]. |
| Reminder of title: |
18th European Conference, Milan, Italy, September 29-October 4, 2024 : proceedings. |
| remainder title: |
ECCV 2024 |
| other author: |
Leonardis, Aleš. |
| corporate name: |
European Conference on Computer Vision |
| Published: |
Cham :Springer Nature Switzerland : : 2025., |
| Description: |
lxxxv, 491 p. :ill. (chiefly color), digital ;24 cm. |
| [NT 15003449]: |
Neural Metamorphosis -- WHAC: World-grounded Humans and Cameras -- Federated Learning with Local Openset Noisy Labels -- Diff3DETR: Agent-based Diffusion Model for Semi-supervised 3D Object Detection -- PSALM: Pixelwise Segmentation with Large Multi-modal Model -- Layout-Corrector: Alleviating Layout Sticking Phenomenon in Discrete Diffusion Model -- Active Coarse-to-Fine Segmentation of Moveable Parts from Real Images -- Topo4D: Topology-Preserving Gaussian Splatting for High-Fidelity 4D Head Capture -- Learning Modality-agnostic Representation for Semantic Segmentation from Any Modalities -- Kinetic Typography Diffusion Model -- Refine, Discriminate and Align: Stealing Encoders via Sample-Wise Prototypes and Multi-Relational Extraction -- Light-in-Flight for a World-in-Motion -- GroupDiff: Diffusion-based Group Portrait Editing -- Faceptor: A Generalist Model for Face Perception -- Inter-Class Topology Alignment for Efficient Black-Box Substitute Attacks -- Segment3D: Learning Fine-Grained Class-Agnostic 3D Segmentation without Manual Labels -- InsMapper: Exploring Inner-instance Information for Vectorized HD Mapping -- KDProR: A Knowledge-Decoupling Probabilistic Framework for Video-Text Retrieval -- Category-level Object Detection, Pose Estimation and Reconstruction from Stereo Images -- Learning with Unmasked Tokens Drives Stronger Vision Learners -- Dual-stage Hyperspectral Image Classification Model with Spectral Supertoken -- Multi-Task Domain Adaptation for Language Grounding with 3D Objects -- Efficient Active Domain Adaptation for Semantic Segmentation by Selecting Information-rich Superpixels -- Efficient Training of Spiking Neural Networks with Multi-Parallel Implicit Stream Architecture -- Camera-LiDAR Cross-modality Gait Recognition -- LiteSAM is Actually what you Need for segment Everything -- IGNORE: Information Gap-based False Negative Loss Rejection for Single Positive Multi-Label Learning. |
| Contained By: |
Springer Nature eBook |
| Subject: |
Computer vision - Congresses. - |
| Online resource: |
https://doi.org/10.1007/978-3-031-72754-2 |
| ISBN: |
9783031727542 |