Computer vision

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

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arXiv AI

Jun 19

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction

arXiv:2603. 01250v2 Announce Type: replace-cross Abstract: Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality.

By Lidia Garrucho, Smriti Joshi, Kaisar Kushibar, Richard Osuala, Maciej Bobowicz, Xavier Bargall\'o, Paulius Jaru\v{s}evi\v{c}ius, Kai Geissler, Raphael Sch\"afer, Muhammad Alberb, Tony Xu, Anne Martel, Daniel Sleiman, Navchetan Awasthi, Hadeel Awwad, Joan C. Vilanova, Robert Mart\'i, Daan Schouten, Jeong Hoon Lee, Mirabela Rusu, Eleonora Poeta, Luisa Vargas, Eliana Pastor, Maria A. Zuluaga, Jessica K\"achele, Dimitrios Bounias, Alexandra Ertl, Katarzyna Gwo\'zdziewicz, Maria-Laura Cosaka, Pasant M. Abo-Elhoda, Sara W. Tantawy, Shorouq S. Sakrana, Norhan O. Shawky-Abdelfatah, Amr Muhammad Abdo-Salem, Androniki Kozana, Eugen Divjak, Gordana Ivanac, Katerina Nikiforaki, Michail E. Klontzas, Rosa Garc\'ia-Dosd\'a, Meltem Gulsun-Akpinar, O\u{g}uz Lafc{\i}, Carlos Mart\'in-Isla, Oliver D\'iaz, Laura Igual, Karim Lekadir

computer-vision benchmarks safety

arXiv Machine Learning

Jun 19

Integrating national forest inventory, airborne lidar, and satellite imagery for wall-to-wall mapping of forest structure with computer vision

arXiv:2606. 20291v1 Announce Type: new Abstract: Remote sensing is increasingly relied upon to deliver actionable science for forest and wildfire risk management across large landscapes.

By Luke J. Zachmann, David D. Diaz, Vincent A. Landau, Chelsey Walden-Schreiner, Tony Chang, Nathan E. Rutenbeck, Katharyn A. Duffy, Kiarie Ndegwa, Andreas Gros, Scott Conway, Guy Bayes

computer-vision

arXiv Machine Learning

Jun 19

Scalable Training of Spatially Grounded 2D Vision-Language Models for Radiology

arXiv:2606. 20477v1 Announce Type: cross Abstract: We study how to train visually grounded vision-language models (VLMs) for radiology without manual spatial annotations.

By Yusuf Salcan (Computer Vision Group, University of Freiburg, Germany, CRIION-AI Lab, Freiburg, Germany), Simon Ging (Computer Vision Group, University of Freiburg, Germany, Adaptive & Agentic AI), Robin Schirrmeister (Department of Radiology, Medical Center -- University of Freiburg, Germany), Philipp Arnold (Department of Radiology, Medical Center -- University of Freiburg, Germany), Elmar Kotter (Department of Radiology, Medical Center -- University of Freiburg, Germany), Behzad Bozorgtabar (Adaptive & Agentic AI), Thomas Brox (Computer Vision Group, University of Freiburg, Germany)

llms computer-vision nlp fine-tuning multimodal benchmarks

arXiv AI

Jun 18

Multi-Modal Hyper-Graph Fusion for Low-Light Crowd Counting

arXiv:2606. 18566v1 Announce Type: cross Abstract: Crowd counting is a fundamental task in computer vision.

By Hao-Yuan Ma, Li Zhang, Yushi Qiu, Jie Gao, Yan Zhang, Bangjun Wang

computer-vision multimodal benchmarks

arXiv Machine Learning

Jun 18

Global Offshore Wind Infrastructure: Deployment and Operational Dynamics from Dense Sentinel-1 Time Series

arXiv:2604. 20822v2 Announce Type: replace-cross Abstract: The offshore wind energy sector is expanding rapidly, increasing the need for independent, high-temporal-resolution monitoring of infrastructure deployment and operation at global scale.

By Thorsten Hoeser, Felix Bachofer, Claudia Kuenzer

computer-vision benchmarks

arXiv AI

Jun 18

A Hybrid LSTM--Vision Transformer Architecture for Predicting HRRR Forecast Errors

arXiv:2606. 19026v1 Announce Type: cross Abstract: Forecast errors in high-resolution numerical weather prediction (NWP) systems are often linked to unresolved planetary boundary layer (PBL) processes, convection, terrain-induced circulations, and other vertically structured atmospheric phenomena.

By David Aaron Evans, Jay C. Rothenberger, Kara J. Sulia, Nick P. Bassill, Chris D. Thorncroft

llms computer-vision safety

arXiv AI

Jun 18

CAOA -- Completion-Assisted Object-CAD Alignment

arXiv:2606. 18429v1 Announce Type: cross Abstract: Accurately aligning CAD models to their corresponding objects in indoor RGB-D scans is a central challenge in 3D semantic reconstruction.

By Hiranya Garbha Kumar, Minhas Kamal, Balakrishnan Prabhakaran

computer-vision benchmarks safety

arXiv Machine Learning

Jun 18

Investigation of Neural Network Methods for Reconstruction and Classification of Texture Images Under Conditions of Incomplete Information

arXiv:2204. 14224v3 Announce Type: replace-cross Abstract: The automated analysis of heterogeneous natural textures is frequently hindered by physical damage and data loss, presenting a significant challenge to computer vision.

By Galymzhan Abdimanap, Kairat Bostanbekov, Abdelrahman Abdallah, Anel Alimova, Darkhan Kurmangaliyev, Daniyar Nurseitov, Tatyana Dedova, Larissa Balakay, Serik Nurakynov

llms agents diffusion computer-vision benchmarks safety

arXiv AI

Jun 18

A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation

arXiv:2605. 17131v2 Announce Type: replace-cross Abstract: Point cloud stands as the most widely adopted format for representing 3D shapes and scenes due to its simplicity and geometric fidelity.

By Minhas Kamal, Hiranya Garbha Kumar, Balakrishnan Prabhakaran

computer-vision benchmarks

arXiv AI

Jun 18

Hardware- and Vision-in-the-Loop Validation of Deep Monocular Pose Estimation for Autonomous Maritime UAV Flight

arXiv:2606. 19176v1 Announce Type: cross Abstract: Autonomous UAV operations on ships require reliable vision-based relative pose estimation, yet at-sea validation is costly, weather-dependent, and risky.

By Maneesha Wickramasuriya, Beomyeol Yu, Jaden Shin, Mason Huslig, Taeyoung Lee, Murray Snyder

llms agents computer-vision

arXiv Machine Learning

Jun 18

Freeing the Law with LOCUS: A Local Ordinance Corpus for the United States

arXiv:2606. 19334v1 Announce Type: cross Abstract: Progress in legal AI increasingly depends on access to authoritative legal text at scale.

By Denis Peskoff, Joe Barrow, Christopher Vu, Diag Davenport

computer-vision

arXiv AI

Jun 18

A Controlled Benchmark of Quantum-Latent GAN Augmentation for Brain MRI

arXiv:2606. 18970v1 Announce Type: cross Abstract: Medical image classification is often constrained by limited labeled data, motivating generative augmentation; recently, quantum generative models have been proposed for this purpose, frequently reporting accuracy gains.

By Syed Mujtaba Haider, Silvia Figini

diffusion computer-vision benchmarks

arXiv AI

Jun 18

ProductConsistency: Improving Product Identity Preservation in Instruction-Based Image Editing via SFT and RL

arXiv:2606. 19103v1 Announce Type: cross Abstract: Recent advances in instruction-based image editing have enabled models to perform complex visual edits from natural language instructions.

By Mukund Khanna, Raj Singh Yadav, Kunal Singh

computer-vision reinforcement-learning fine-tuning benchmarks

arXiv AI

Jun 18

Spotlight: Synergizing Seed Exploration and Spot GPUs for DiT RL Post-Training

arXiv:2606. 19004v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training of Diffusion Transformers (DiTs) is prohibitively expensive, requiring thousands of high-end GPUs.

By Ruiqi Lai, Dakai An, Wei Gao, Ju Huang, Siran Yang, Jiamang Wang, Lin Qu, Dmitrii Ustiugov, Wei Wang

llms diffusion computer-vision reinforcement-learning

arXiv Machine Learning

Jun 18

Quantification of Uncertainty with Adversarial Models in Medical Image Segmentation

arXiv:2606. 18860v1 Announce Type: cross Abstract: Reliable pixel-level uncertainty quantification holds the potential to transform clinical workflows by enabling high-fidelity longitudinal monitoring and distinguishing true pathological changes from artifacts.

By Hana Jebril, Thomas Pinetz, G\"unter Klambauer, Hrvoje Bogunovi\'c

computer-vision safety

arXiv Machine Learning

Jun 18

Structural MRI Synthesis for Alzheimer's Disease via Conditional Diffusion on Anatomical Masks

arXiv:2606. 18354v1 Announce Type: cross Abstract: Recent advances in generative machine learning models have significantly improved medical imaging, offering promising solutions for data augmentation, privacy preservation, and improved model generalization.

By Muge Zhang, Muhammad Ali Khaliq, Jamal Alsakran, Byeong Kil Lee, Jeeho Ryoo

diffusion computer-vision safety

arXiv Machine Learning

Jun 18

Transformer Geometry Observatory TGO-I: Spectral Geometry Observatory

arXiv:2606. 19249v1 Announce Type: cross Abstract: Despite the widespread adoption of Vision Transformers (ViTs) and their success across numerous computer vision applications, the fundamental understanding of their dimensional and representational geometry remains relatively underexplored.

By Kaustubh Kapil, Kishor P. Upla

llms computer-vision

arXiv AI

Jun 18

LandslideAgent with Multimodal LandslideBench: A Domain-Rule-Augmented Agent for Autonomous Landslide Identification and Analysis

arXiv:2606. 18661v1 Announce Type: cross Abstract: Intelligent landslide hazard interpretation is critical for disaster prevention, yet current paradigms struggle to simultaneously extract visual features and high-level geoscientific semantics, while general-purpose vision-language models (VLMs) suffer from perceptual limitations and domain hallucinations in complex geological scenarios.

By Chengfu Liu, Dongyang Hou, Junwu Xiang, Cheng Yang, Xuezhi Cui, Zeyuan Wang, Liangtian Liu, Zelang Miao

llms agents computer-vision fine-tuning multimodal safety

arXiv Machine Learning

Jun 18

Clinically Aligned Geometry Constraints for Robust IVUS Vessel Boundary Segmentation

arXiv:2606. 18723v1 Announce Type: cross Abstract: Intravascular ultrasound (IVUS) lumen and external elastic membrane (EEM) segmentation is important for quantitative coronary plaque burden assessment.

By Yunshu Chen, Litao Yang, Giuseppe Di Giovanni, Jordan Tan, Deval Mehta, Andrew Lin, Derek Chew, Masasi Fujino, Julie Butters, Stephen Nicholls, Zongyuan Ge, Kyung Hoon Cho

computer-vision

arXiv Machine Learning

Jun 18

Confidence is Not Reliability: Rethinking MC Dropout in Brain Tumour Segmentation

arXiv:2606. 19300v1 Announce Type: cross Abstract: Glioma segmentation in multiparametric MRI is a critical component of treatment planning.

By Xin Ci Wong, Duygu Sarikaya, Kieran Zucker, Marc De Kamps, Nishant Ravikumar

computer-vision safety

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