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3,462 papers
A reliability protocol for small-cohort benchmarks that separates reproducible effects from differences the evaluation cannot resolve, and is cheap enough to accompany any evaluation on such a resource and separate reproducible effects from differences the evaluation cannot resolve.
Across scene-level 3D object detection, object pose estimation, and scene reconstruction, Lucida improves mAP over Boxer by 69% on R2S-Scene, raises ADD-SB@0.05 from 57.8% to 83.4% on CA-1M, and increases scene F-Score from 0.794 for SAM3D to 0.924.
Experimental evaluation shows that composition-aware pretraining yields substantial gains on region-level understanding tasks requiring semantic similarity judgment, including zero-shot image retrieval and scene classification, while remaining competitive on tasks requiring fine-grained spatial precision, such as segme...
A generative-augmented detection paradigm that leverages multimodal image generation to enrich the feature space of rare and small objects and outperforms existing state-of-the-art methods for small-object detection in safety-critical applications is proposed.
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RailSyn, a diagnosis-guided framework comprising a real-referenced Inspector and a requirement-aligned Generator, that addresses railway-context, intrusion-semantic, and visual-consistency requirements through domain adaptation, agent-planned placement and physical contact relations, and plan-consistent conditional ref...
This work formulates active learning for VG under the realistic setting where only raw images are available without accompanying text, and introduces Referred Region Ambiguity, a new acquisition function that measures whether the model's confidence collapses onto a single region or disperses across multiple candidates.
A novel Diffusion-guided Sampling for Consensus-based Robust Estimation (DiffSAC) framework that refines the confidence for each data point, indicating whether it belongs to a good minimum set, rather than ranking the data points as in previous work, significantly reduces the need to process numerous bad sets.
SlideCRF is proposed, which adapts conditional random fields for whole-slide images by combining spatial and biological cues while accounting for classes that may be absent from a given slide, and provides a set of realistic annotation protocols, based on spatially localized clicks and scribbles, modeling different pat...
SePArate, a weakly supervised wafer defect segmentation method, enables pixel-level separation of patterns by leveraging only image-level annotations and outperforms the baselines.
A new dataset of voxel-wise annotations of the vessel lumen and coronary segments, alongside centerlines, and mesh surfaces for 800 scans from the publicly available ImageCAS dataset is provided to support the development and validation of methods for lumen segmentation, plaque and perivascular quantification, and haem...
This work decomposes video into view-invariant and view-variant latents and recompose them under language supervision encouraging clean decomposition of the two streams, and proposes PRISM, that achieves state-of-the-art results on EgoExo4D, EgoExoLearn, AE2, even surpassing in-domain models under zero-shot setting.
By combining HRAP with RMR, ScenePilot offers an efficient alternative to one-shot generation and heavy full-scene optimization, improving physical plausibility, functional coherence, and controllability while preserving diversity.
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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