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3,462 papers
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.
This work introduces SpatialBlock-15k, a synthetic dataset of 15,000 block-stacking problems covering 3D-to-2D projection, viewpoint transformation, and structural combination and proposes a novel paradigm inspired by human cognitive development: learning foundational spatial skills through structured block-manipulatio...
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LoGAN, a VLM-based agentic framework for few-shot multilingual font localization, which takes in a small number of individual glyphs from a font or letters from a logo and uses them to generate complete character sets in other languages, achieves broad language coverage for font localization with various styles.
By mitigating implant-related artifacts, ARNAI improved segmentation and downstream measurement accuracy, with the greatest benefit observed for L4--L5 segmental Cobb angle estimation, where the mean error was reduced by approximately 70%.
The introduction of AV-SafetyBench, the first safety benchmark developed specifically for T2AV generation, is introduced and the value of AV-SafetyBench for evaluating T2AV safety across the visual and audio modalities and their interaction is demonstrated.
This work addresses limitations in transfer learning for vision-language models through transformation-aware prompt conditioning and a re-calibrated contrastive loss, and treats same-class samples as positives rather than distinct instances, enabling the model to learn domain-specific features more effectively.
DPSF-Net is proposed, a dual-prior spatial-frequency network built on MCAF-Net for real-world RSID that achieves state-of-the-art performance on the real-world RRSHID remote sensing image dehazing benchmark and remains competitive across multiple synthetic datasets.
A regularize-then-enrich interaction is revealed: multi-scale features alone do not improve final segmentation, yet become highly effective when coupled with spatial regularization, underscoring that spatial coherence is aprerequisite for multi-scale representations in superpoint clustering.
This work introduces Emo-DVS, the first large-scale event-based emotion analysis dataset, which couples dynamic illumination with the Facial Action Unit (FAU) subset and emotion subset and proposes the Information-Guided Gated Fusion (IGF) framework, which achieves state-of-the-art performance.
A structure-aware federated learning framework for catheter and guidewire analysis is presented, supporting collaborative training without centralising patient data or large amounts of manual annotation.
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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