Computer vision

Detection, segmentation, depth and recognition research, plus the vision backbones that keep displacing the last generation.

3,379 stories · RSS feed

arXiv Computer Vision
Sep 22

AWR-Net: Decoupling Anatomy and Appearance for 3D Fetal Brain Ultrasound Synthesis

The paper introduces AWR-Net, a two‑stage framework that decouples anatomy and appearance to synthesize realistic 3D fetal brain ultrasound volumes from anatomical label maps. The first stage uses wavelet diffusion to generate volumes from atlas pairs in the wavelet domain, while the second stage applies residual refinement in the image domain to adapt to real ultrasound appearance. Experiments on real fetal brain ultrasound data show that AWR‑Net outperforms existing synthesis methods, improving metrics such as normalized cross‑correlation and Fréchet Inception Distance, and also enhances downstream segmentation, especially for severe abnormal cases.

By Yuhuan Lu, Sergio Valencia, Yuanji Zhang, Yuhao Huang, Camilo Jaimes, P. Ellen Grant, Davood Karimi
arXiv Computer Vision
Sep 22

Ev-YOLO: Uncertainty-Aware Object Detection via a Unified Evidential Formulation

arXiv:2609.24668v1 Announce Type: new Abstract: Reliable uncertainty estimation is essential for deploying object detectors in autonomous systems operating in uncertain environments. Evidential Deep...

By Simon Barbarit-Gaboriau (LITIS - STI, INSA Rouen Normandie), Hind Laghmara (LITIS - STI), R\'emi Boutteau (LITIS - STI), Samia Ainouz (LITIS, LITIS - STI)
arXiv Computer Vision
Sep 22

Applications of Neural Cellular Automata: State of the Art, Challenges and Opportunities

arXiv:2609.24595v1 Announce Type: new Abstract: Neural Cellular Automata (NCAs) are a new type of neural network architecture which enable accurate and robust inference at extremely small model sizes...

By Nick Lemke, Niklas Ihm, John Kalkhof, Mirko Konstantin, Henry J. Krumb, Daniel M. Lang, Ehsan Pajouheshagar, Ario Sadafi, Arjan Kuijper, Karim Lekadir, Marco Lorenzi, Carsten Marr, Julia A. Schnabel, Anirban Mukhopadhyay
arXiv Computer Vision
Sep 22

Document Retrieval-Aware Chunking (D-RAC): Universal Retrieval-Aware Ingestion of Enterprise Documents via PDF Normalization and Multimodal Markdown Conversion

arXiv:2609.24220v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems over enterprise knowledge bases must ingest heterogeneous document formats -- PDFs, Word documents, presen...

By Uday Allu (AI Research Team Yellow.ai), Abhivanth Sivaprakash (AI Research Team Yellow.ai), Pratik Singh (AI Research Team Yellow.ai), Aman Manocha (AI Research Team Yellow.ai)
arXiv Machine Learning
Sep 22

Reinforcement Learning Inspired Black-box Adversarial Attacks for Computer Vision

The paper introduces RIBA, a reinforcement‑learning inspired black‑box adversarial attack that generates perturbations for neural networks with fewer queries than existing methods. RIBA achieves a 25.4% reduction in median queries on ResNet‑18/Cifar10 and a 22.5% reduction on Vit‑B/16/ImageNet, while matching white‑box attack performance on an adversarially trained model.

By Florian Krone, Elena Hoemann, Sven Hallerbach