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3,385 papers
This work introduces a latent-to-latent flow technique for stochastic segmentation of medical volumes via encoded representations of both the image and label space, improving efficiency up to 14x compared with full resolution models while maintaining clinically relevant performance.
A lightweight federated MIL-VLM cascade in which only a compact MIL scorer is trained across clients, while a frozen VLM verifies high-scoring suspect segments post hoc is introduced.
Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed optimization, or single-image generative models that ignore crucial multi-view cues necessary for understanding 3D geometry and material interactions. To address these limitations, we introduce a feed-forward...
A hybrid two-stage architecture that combines a federated binary convolutional neural network (CNN) gate with server-side zero-shot VLM inference and routing rules can be adjusted to trade server-side VLM usage for higher anomaly sensitivity is proposed.
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BlueprintAgent (BPA), a constraint-triggered multimodal agent for simulation-ready frame extraction from scanned blueprints, is presented, which treats the MLLM as the primary reader and decision maker, with OCR and computer vision supplying localized evidence.
D3ARC is introduced, an asynchronous distributed hierarchical framework for time-aware and reliable wildfire detection that introduces a forward-looking capability that allows agents to anticipate the future by evaluating candidate strategies before execution.
MV-STRIDE, a Multi-View hierarchical SpaTial Reasoning dataset with Interdependent and DEcomposed capabilitiEs, explicitly models the dependency relationships between foundational perception, scene understanding, and complex contextual reasoning, providing a coherent learning pathway aligned with human spatial cognitio...
The initial findings highlight the potential of combining deep learning and dermatoscopy to provide a biopsy- free alternative for BCC subtyping, thus aiding in improving treatment planning and patient outcomes.
FACTS, a structured Fisher Approximation tailored to Compressing ViTs with Fisher-weighted SVD, which enforces token-local aggregation while preserving within-token activation-gradient dependence, and introduces a fast Constrained Rank Search (CoRS), that optimizes layer-wise rank allocation while adhering to a fixed f...
This work proposes Flow3D-OPD, a two-stage post-training framework that introduces multi-teacher distillation into 3D geometry generation and achieves consistent improvements across all geometric quality dimensions and surpasses all teacher models in the average metric.
ASA is proposed, a query-based black-box framework that searches over natural-language editing scenarios using a multimodal language model and a modern text-guided generative editor and uses a greedy explorer to compose only attack-improving scenarios.
This submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge is presented, which ranked first in the large-model division and second in the<=2B division, suggesting that visual grounding is more important than annotation volume for this task.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
Human-Computer Interaction and Visualization
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