Computer vision

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

1,466 stories · RSS feed

arXiv AI

Jul 10

GAP-GDRNet: Geometry-aware monocular 6D pose estimation for spacecraft using synthetic geometric supervision

arXiv:2607. 02360v3 Announce Type: replace-cross Abstract: Monocular spacecraft 6D pose estimation remains difficult under weak texture, thin structures, illumination variation, and occlusion.

By Zongwu Xie, Yonglong Zhang, Yifan Yang, Yang Liu, Guanghu Xie

computer-vision benchmarks

arXiv Machine Learning

Jul 10

False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation

arXiv:2607. 07852v1 Announce Type: cross Abstract: Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy.

By Linus Juni, Aasa Feragen, Aditya Parikh

computer-vision safety

arXiv AI

Jul 10

An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation

arXiv:2602. 13376v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly used in document processing pipelines to convert flowchart images into structured code (e.

By Giang Son Nguyen, Zi Pong Lim, Sarthak Ketanbhai Modi, Yon Shin Teo, Wenya Wang

llms computer-vision multimodal

arXiv AI

Jul 10

Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction

arXiv:2607. 08725v1 Announce Type: cross Abstract: Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable.

By Ayda Eghbalian, Kevin Desai

llms computer-vision multimodal benchmarks

arXiv Machine Learning

Jul 10

Holographic Neural PCFG for Unsupervised Parsing

arXiv:2607. 08063v1 Announce Type: cross Abstract: Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone.

By Ryosuke Yamaki, Daichi Mochihashi, Nobutaka Shimada, Tadahiro Taniguchi

rag computer-vision benchmarks

arXiv Machine Learning

Jul 10

Image classification via a quantum-inspired strategy involving a mixture of experts

arXiv:2607. 07754v1 Announce Type: new Abstract: Pattern recognition problems arise in a variety of physical image processing situations, and convolutional neural networks are a popular scheme for the required feature extraction and classification tasks.

By Kumari Jyoti, Rohith Babu, Apoorva D. Patel

diffusion computer-vision benchmarks

arXiv AI

Jul 10

Conversational AI for Rapid Scientific Prototyping: A Case Study on ESA's ELOPE Competition

arXiv:2601. 04920v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as coding partners, yet their role in accelerating scientific discovery remains underexplored.

By Nils Einecke

llms computer-vision

arXiv AI

Jul 10

Time-to-Collision Based Dynamic Obstacle Avoidance Using Pretrained Vision Models for Robots in Unstructured Environments

arXiv:2607. 07885v1 Announce Type: cross Abstract: Dynamic obstacle avoidance in unstructured outdoor environments remains a critical challenge for autonomous mobile robots, particularly when large-scale robot-specific training data and simulation-based policies are impractical.

By Erik Jagnandan, Mulugeta Haile, Gregory Barber, Pratik Chaudhari

agents computer-vision robotics

arXiv Machine Learning

Jul 10

On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection

arXiv:2607. 08391v1 Announce Type: cross Abstract: Making tradeoffs between execution latency and result utility (i.

By Ahmet Soyyigit, Shuochao Yao, Heechul Yun

agents computer-vision robotics

arXiv Machine Learning

Jul 10

Beyond Backpropagation: Monte Carlo Method Can Train Deep Neural Networks

arXiv:2607. 08406v1 Announce Type: new Abstract: Backpropagation (BP) dominates deep learning training, but its reliance on gradients brings inherent troubles -- vanishing and exploding gradients.

By Hong Zhao

llms computer-vision efficiency

arXiv AI

Jul 10

MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection

arXiv:2511. 12810v2 Announce Type: replace-cross Abstract: Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend seamlessly into their environments due to high similarity in color, texture, and size.

By Leena Alghamdi, Muhammad Usman, Hafeez Anwar, Abdul Bais, Saeed Anwar

llms computer-vision benchmarks

arXiv Machine Learning

Jul 10

ConRad: Efficient Conformal Prediction for Radiomics

arXiv:2607. 08084v1 Announce Type: cross Abstract: Radiomic features derived from medical images and segmentation masks are used to support decision making in clinical imaging pipelines.

By Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan

computer-vision benchmarks

arXiv AI

Jul 10

Agentic Neural Architecture Search

arXiv:2607. 07984v1 Announce Type: new Abstract: Neural architecture search (NAS) methods have grown increasingly efficient, yet they remain bounded by manually engineered search spaces that require substantial domain expertise and must be rebuilt for every new task.

By Seokhoon Jeong, Mijung Kim, Taehwan Kim

llms agents computer-vision benchmarks

arXiv AI

Jul 10

OREN: Octree Residual Network for Real-Time Euclidean Signed Distance Mapping

arXiv:2510. 18999v3 Announce Type: replace-cross Abstract: Reconstructing signed distance functions (SDFs) from point cloud data benefits many robot autonomy capabilities, including localization, mapping, motion planning, and control.

By Zhirui Dai, Qihao Qian, Tianxing Fan, Nikolay Atanasov

computer-vision robotics

arXiv AI

Jul 10

Leveraging Color Naming for Image Enhancement

arXiv:2607. 08185v1 Announce Type: cross Abstract: Enhancing images to make them visually appealing is a persistent challenge in computer vision.

By David Serrano-Lozano, Luis Herranz, Michael S. Brown, Javier Vazquez-Corral

llms computer-vision benchmarks safety

arXiv AI

Jul 10

Infinity-Parser2 Technical Report

arXiv:2607. 07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end-to-end document parsing, addressing the persistent scarcity of faithfully annotated parsing corpora.

By Zuming Huang, Jun Huang, Kexuan Ren, Baode Wang, Weizhen Li, Jianming Feng, Yu Wang, Yichen Yao, Shijun Lin, Yige Tang, Cheng Peng, Weidi Xu, Wei Chu, Yinghui Xu, Yuan Qi

computer-vision reinforcement-learning efficiency multimodal benchmarks

arXiv AI

Jul 10

LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection

arXiv:2607. 08076v1 Announce Type: cross Abstract: The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions.

By Wenhao Dong, Xiaoyan Luo, Linlin Yang, Haodong Zhu, Xiaorong Shi, Guodong Guo, Baochang Zhang

computer-vision multimodal benchmarks

arXiv AI

Jul 10

TMI: Text-to-Image Meets Image-to-Image for Complementary Data Synthesis to Boost Long-Tailed Instance Segmentation

arXiv:2607. 08201v1 Announce Type: cross Abstract: Large-vocabulary instance segmentation is constrained by long-tailed category distributions and fine-grained inter-class ambiguity.

By Hyeonseop Song, Seokhun Choi, Hoseok Do

diffusion computer-vision benchmarks

arXiv AI

Jul 10

ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents

arXiv:2607. 08143v1 Announce Type: cross Abstract: We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents.

By Maud Ehrmann, Emanuela Boros, Juri Opitz, Andrianos Michail, Florian Wagner, Simon Clematide

llms computer-vision fine-tuning

Hugging Face Trending Papers

Jul 10

CHM-Net: Center Heatmap-driven Macro-Micro Modeling Network for MRI-based Microbial Density Stratification

Microbial density is clinically important for tumor assessment and treatment decision-making, and recent advances in deep learning suggest that it can be non-invasively inferred from multimodal MRI. In this work, MRI-based Microbial Density Stratification (MRI-MDS) is first investigated as a patient-level representation learning task, and Center Heatmap-driven Macro-micro modeling Network (CHM-Net) is introduced for this task.

computer-vision multimodal