Computer Vision – ECCV 2024 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LXXXIII /
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully review...
I tiakina i:
| Kaituhi rangatōpū: | |
|---|---|
| Ētahi atu kaituhi: | , , , , , |
| Hōputu: | Tāhiko īPukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
|
| Putanga: | 1st ed. 2025. |
| Rangatū: | Lecture Notes in Computer Science,
15141 |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1007/978-3-031-73010-8 |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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MARC
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| 245 | 1 | 0 | |a Computer Vision – ECCV 2024 |h [electronic resource] : |b 18th European Conference, Milan, Italy, September 29–October 4, 2024, Proceedings, Part LXXXIII / |c edited by Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
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| 490 | 1 | |a Lecture Notes in Computer Science, |x 1611-3349 ; |v 15141 | |
| 505 | 0 | |a LG-Gaze: Learning Geometry-aware Continuous Prompts for Language-Guided Gaze Estimation -- Efficient Training with Denoised Neural Weights -- Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning -- Integration of Global and Local Representations for Fine-grained Cross-modal Alignment -- Local and Global Flatness for Federated Domain Generalization -- SRPose: Two-view Relative Pose Estimation with Sparse Keypoints -- Deep Reward Supervisions for Tuning Text-to-Image Diffusion Models -- Paying More Attention to Images: A Training-Free Method for Alleviating Hallucination in LVLMs -- Inf-DiT: Upsampling any-resolution image with memory-efficient diffusion transformer. -- Implicit Neural Models to Extract Heart Rate from Video -- Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering -- PFGS: High Fidelity Point Cloud Rendering via Feature Splatting -- Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation -- E3M: Zero-Shot Spatio-Temporal Video Grounding with Expectation-Maximization Multimodal Modulation -- EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions -- LMT-GP: Combined Latent Mean-Teacher and Gaussian Process for Semi-supervised Low-light Image Enhancement -- Veil Privacy on Visual Data: Concealing Privacy for Humans, Unveiling for DNNs -- Efficient Vision Transformers with Partial Attention -- Generalized Coverage for More Robust Low-Budget Active Learning -- Rasterized Edge Gradients: Handling Discontinuities Differentially -- Enhancing Cross-Subject fMRI-to-Video Decoding with Global-Local Functional Alignment -- FedTSA: A Cluster-based Two-Stage Aggregation Method for Model-heterogeneous Federated Learning -- LLaVA-UHD: an LMM Perceiving any Aspect Ratio and High-Resolution Images -- Learning Natural Consistency Representation for Face Forgery Video Detection -- ZeroI2V: Zero-Cost Adaptation of Pre-Trained Transformers from Image to Video -- Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems -- R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model. | |
| 520 | |a The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation. | ||
| 588 | |a Print version record. | ||
| 650 | 0 | |a Image processing |x Digital techniques. | |
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Computer networks . | |
| 650 | 0 | |a User interfaces (Computer systems). | |
| 650 | 0 | |a Human-computer interaction. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Computers, Special purpose. | |
| 650 | 1 | 4 | |a Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 650 | 2 | 4 | |a Computer Communication Networks. |
| 650 | 2 | 4 | |a User Interfaces and Human Computer Interaction. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Special Purpose and Application-Based Systems. |
| 700 | 1 | |a Leonardis, Aleš. |e editor. |0 (orcid)0000-0003-0773-3277 |1 https://orcid.org/0000-0003-0773-3277 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Ricci, Elisa. |e editor. |0 (orcid)0000-0002-0228-1147 |1 https://orcid.org/0000-0002-0228-1147 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Roth, Stefan. |e editor. |0 (orcid)0000-0001-9002-9832 |1 https://orcid.org/0000-0001-9002-9832 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Russakovsky, Olga. |e editor. |0 (orcid)0000-0001-5272-3241 |1 https://orcid.org/0000-0001-5272-3241 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Sattler, Torsten. |e editor. |0 (orcid)0000-0001-9760-4553 |1 https://orcid.org/0000-0001-9760-4553 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Varol, Gül. |e editor. |0 (orcid)0000-0002-8438-6152 |1 https://orcid.org/0000-0002-8438-6152 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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