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3,080 papers
This is the first study to formulate image-grounded review assistance as a multi-agent vision-language reasoning problem, providing a practical step toward AI-assisted review authoring in e-commerce systems.
This work proposes a VLM-driven agentic framework for semantic compositional SVG generation that recursively parses visual scenes into semantic and geometric hierarchies via top-down decomposition, visual grounding, and prompt-driven amodal occlusion recovery, ensuring each component is geometrically complete.
Open-UniMo, a unified Large Motion-Language Model (LMLM) trained on million-scale open-world motion-language data, and Open-MoBench, a VLM-guided benchmark for assessing text-to-motion (T2M) generation, motion-to-text (M2T) understanding, and bidirectional consistency are proposed.
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into collecting, centralizing, and sharing pathology imaging data. In contrast, sharing of image-derived data such as region-of-interest delineatio...
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Parkinson's disease (PD) manifests early neuromotor impairments that become observable in controlled hand-drawn patterns such as spirals and meanders, where tremor-induced oscillations, stroke irregularity, and curvature instability reflect underlying motor degradation. In this work, we present an explainable framework...
WAVIE (Wavelet Augmented Vision Intermediate Embeddings) is proposed, an end-to-end architecture that combines complementary spatial and frequency cues on top of a frozen CLIP backbone that outperforms several state-of-the-art generalization baselines for deepfake detection in the wild.
A generative AI integrated multimodal ReID framework designed explicitly for robustness under missing cues and low latency deployment is proposed, with a cost aware early-exit cascade that prioritizes inexpensive, high confidence evidence and only triggers expensive modalities for ambiguous cases.
SpermYOLO is an effective and efficient approach for sperm detection in challenging microscopic imaging scenarios and introduces four architectural improvements: C3k2-IDB for channel-wise discriminative feature extraction, D2SEM for spatial--spectral semantic enhancement, MFM for adaptive multi-scale feature fusion, an...
High-mix low-volume (HMLV) manufacturing requires inspection systems to adapt to changing parts, specifications, and work orders without repeated task-specific programming. Existing inspection automation typically assumes predefined sensing sequences, while general purpose robot agents optimize task completion rather t...
An improved BEV 3D object detection algorithm Sparse-BEVNet is proposed, which introduces a Bi-Level Routing Attention mechanism into the image feature extraction network to reduce the computational burden of the backbone and employs Cascaded Group Attention in the feature fusion module.
This paper reformulates TTM as an online, frame-level prediction task, instead of treating TTM as a binary problem against a single negative class, and model it in the presence of diverse and previously underexplored non-TTM states, such as talking-to-others, self-talking, and background conditions.
A voxel-spacing-aware extension of PyRadiomics that incorporates spacing information without generating interpolated gray levels is implemented and validated, providing a backward-compatible technical basis for future evaluation of spacing-aware radiomics in heterogeneous medical imaging datasets.
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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