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…mehr
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.
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Inhaltsangabe
How to Train the Teacher Model for Effective Knowledge Distillation.- Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers.- Deciphering the Role of Representation Disentanglement: Investigating Compositional Generalization in CLIP Models.- Modality Translation for Object Detection Adaptation without forgetting prior knowledge.- FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning.- Learning Multimodal Latent Generative Models with Energy-Based Prior.- On Learning Discriminative Features from Synthesized Data for Self-Supervised Fine-Grained Visual Recognition.- LaWa: Using Latent Space for In-Generation Image Watermarking.- Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution.- Markov Knowledge Distillation: Make Nasty Teachers trained by Self-undermining Knowledge Distillation Fully Distillable.- Co-speech Gesture Video Generation with 3D Human Meshes.- When and How do negative prompts take effect?.- GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views.- CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting.- Snuffy: Efficient Whole Slide Image Classifier.- Learning to Build by Building Your Own Instructions.- Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling.- BlenderAlchemy: Editing 3D Graphics with Vision-Language Models.- D pS: Delayed -Shrinking for Faster Once-For-All Training.- Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models.
How to Train the Teacher Model for Effective Knowledge Distillation.- Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers.- Deciphering the Role of Representation Disentanglement: Investigating Compositional Generalization in CLIP Models.- Modality Translation for Object Detection Adaptation without forgetting prior knowledge.- FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning.- Learning Multimodal Latent Generative Models with Energy-Based Prior.- On Learning Discriminative Features from Synthesized Data for Self-Supervised Fine-Grained Visual Recognition.- LaWa: Using Latent Space for In-Generation Image Watermarking.- Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution.- Markov Knowledge Distillation: Make Nasty Teachers trained by Self-undermining Knowledge Distillation Fully Distillable.- Co-speech Gesture Video Generation with 3D Human Meshes.- When and How do negative prompts take effect?.- GS2Mesh: Surface Reconstruction from Gaussian Splatting via Novel Stereo Views.- CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting.- Snuffy: Efficient Whole Slide Image Classifier.- Learning to Build by Building Your Own Instructions.- Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling.- BlenderAlchemy: Editing 3D Graphics with Vision-Language Models.- D pS: Delayed -Shrinking for Faster Once-For-All Training.- Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models.
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