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Recent ECCV 2026 acceptances: Shared LoRA Subspaces (first author) and Perceptual Taxonomy (senior author).
Two-line summary of the contribution and scope.
An ECCV 2026 framework for evaluating hierarchical scene reasoning in vision-language models.
Joint 3D part segmentation and semantic naming.
Part segmentation learned from synthetic animal data.
A comprehensive dataset for 3D animal pose and shape.
Shared weight-subspace structure for efficient adaptation and continual learning.
Resource-efficient adaptation and inference via adapter recycling.
An ECCV 2026 shared-subspace approach toward almost strict continual learning for large models.
Continual learning with optimal relevance mapping.
Incremental neural mesh models for class-incremental learning.
Adaptive neural connectivity for sparsity-aware learning.
Failure-aware multiview 3D consistency metrics for hallucination-prone foundation reconstruction models.
Scaling compositional models for robust 3D classification and pose.
Source-free domain adaptation for category-level pose estimation.
Bayesian OOD robustness in image classification.
Fast 4D generation through diffusion-based triplane re-posing.
Pose-free sparse-view scene reconstruction using diffusion priors.
Improved alignment in text-to-image generative models.
Offline outdoor navigation with full privacy.
Timing attack analysis on AES on modern processors.
Real-time neural model-based human detection and behavior classification.
An ECCV 2026 shared-subspace approach toward almost strict continual learning for large models.
An ECCV 2026 framework for evaluating hierarchical scene reasoning in vision-language models.
Failure-aware multiview 3D consistency metrics for hallucination-prone foundation reconstruction models.
Joint 3D part segmentation and semantic naming.
Shared weight-subspace structure for efficient adaptation and continual learning.
Scaling compositional models for robust 3D classification and pose.
Fast 4D generation through diffusion-based triplane re-posing.
Pose-free sparse-view scene reconstruction using diffusion priors.
Improved alignment in text-to-image generative models.
Resource-efficient adaptation and inference via adapter recycling.
Incremental neural mesh models for class-incremental learning.
Part segmentation learned from synthetic animal data.
Source-free domain adaptation for category-level pose estimation.
Bayesian OOD robustness in image classification.
A comprehensive dataset for 3D animal pose and shape.
Continual learning with optimal relevance mapping.
Adaptive neural connectivity for sparsity-aware learning.
Real-time neural model-based human detection and behavior classification.
Offline outdoor navigation with full privacy.
Timing attack analysis on AES on modern processors.
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