Computer vision

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

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arXiv Machine Learning

Jul 14

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

arXiv:2607. 09812v1 Announce Type: cross Abstract: 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.

By Jiaming Liang, Haolin Chen, Tingting Li, Bowen Yu, Qianyan Long, Tinghe Zhang, Xi Zhong, Xiaowei Hu, Xiaoqi Sheng, Hongmin Cai

computer-vision multimodal

arXiv AI

Jul 14

The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy

arXiv:2607. 10388v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming electron microscopy by enabling quantitative analysis of increasingly large and complex datasets for nanoparticle characterization.

By Evropi Toulkeridou, Jiafei Li, Leonardo Lari, Panagiotis Grammatikopoulos

llms agents computer-vision multimodal benchmarks

arXiv Machine Learning

Jul 14

Adversarially Guided Diffusion for LiDAR Range Image Synthesis

arXiv:2607. 09787v1 Announce Type: cross Abstract: LiDAR semantic segmentation is a key perception task in autonomous driving, where false predictions can affect downstream planning and safety-critical decision-making.

By Stavros Bouras, Antonios Makris, Alexandros Gkillas, Aris S. Lalos, Konstantinos Tserpes

agents diffusion computer-vision robotics safety

arXiv AI

Jul 14

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation

arXiv:2604. 15271v3 Announce Type: replace-cross Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decision support.

By Tianhao Fu, Austin Wang, Charles Chen, Roby Aldave-Garza, Yucheng Chen

computer-vision

arXiv Machine Learning

Jul 14

Gradient-Skipping Relevance Propagation for Efficient Explainability of Vision Transformers

arXiv:2607. 10365v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are difficult to interpret because current methods of relevance propagation and attention flow do not fully consider some key architectural features, such as the uneven importance of attention heads and residual connections.

By Christopher Buratti, Michele Marchetti, Federica Parlapiano, Davide Traini, Domenico Ursino, Luca Virgili

llms computer-vision benchmarks safety

arXiv AI

Jul 14

VehAnchor: Metadata-Free Metric Scale Recovery from Vehicle Cues in Aerial Imagery

arXiv:2603. 04277v2 Announce Type: replace-cross Abstract: Autonomous aerial robots operating in GPS-denied or communication-degraded environments frequently lose access to camera metadata and telemetry, leaving onboard perception systems unable to recover the absolute metric scale of the scene.

By Yifei Chen, Chenqian Le, Jiayi Cheng, Xupeng Chen

llms agents computer-vision robotics multimodal benchmarks safety

arXiv Machine Learning

Jul 14

BiLoG-Net: A Bi-Context Location-Guided Network for Breast Mass Segmentation and Malignancy Classification in Mammography

arXiv:2607. 10188v1 Announce Type: cross Abstract: Breast cancer remains the most commonly diagnosed malignancy among women worldwide, yet accurate detection and characterization of breast masses in mammography remain challenging due to subtle intensity variations, heterogeneous tissue densities, and indistinct lesion boundaries that complicate radiological interpretation.

By Abu Fatema Mohammad Abdun Noor, Md Imam Ahasan, Md Samiul Ahasan, Kah Ong Michael Goh, S M Hasan Mahmud, Raihana Zannat

llms computer-vision benchmarks

arXiv AI

Jul 14

FlowPainter: Inpainting Optical Flow via Confidence-Guided Completion

arXiv:2607. 10140v1 Announce Type: cross Abstract: Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation.

By Yuang Meng, Chenyang Wu, Xianshun Liu, Chun-Le Guo, Zichen Liang, Lina Lei, Jie Liang, Hui Zeng, Chongyi Li, Lei Zhang

diffusion computer-vision benchmarks

arXiv Machine Learning

Jul 14

Monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification

arXiv:2510. 25573v2 Announce Type: replace-cross Abstract: Machine learning approaches for image classification have led to impressive advances in that field.

By Christopher T. Franck, Anne R. Driscoll, Zoe Szajnfarber, William H. Woodall

computer-vision

arXiv AI

Jul 14

SCALECUA: Scaling Computer Use Agents with Verifiable Task Synthesis and Efficient Online RL

arXiv:2607. 11185v1 Announce Type: new Abstract: Computer use agents (CUAs) are emerging as a powerful interface for automating complex digital workflows through visual perception and GUI execution.

By Bowen Lv, Xiao Liu, Yanyu Ren, Hanyu Lai, Bohao Jing, Hanchen Zhang, Yanxiao Zhao, Shuntian Yao, Jie Tang, Yuxiao Dong

agents computer-vision reinforcement-learning benchmarks

arXiv Machine Learning

Jul 14

Student Capacity Moderates Knowledge Distillation Effectiveness: A Systematic Study Across ResNet Teacher-Student Pairs on CIFAR-10

arXiv:2605. 31191v2 Announce Type: replace Abstract: We investigate how teacher-student capacity relationships modulate knowledge distillation (KD) effectiveness in ResNet-based image classification on CIFAR-10.

By Umut Onur Yasar

computer-vision efficiency

arXiv AI

Jul 14

Evidence-Backed Video Question Answering

arXiv:2607. 11862v1 Announce Type: cross Abstract: Current Video Large Language Models (Video LLMs) excel in question answering (QA) but largely operate as black boxes, providing textual answers without verifiable visual grounding.

By Shijie Wang, Honglu Zhou, Ziyang Wang, Ran Xu, Caiming Xiong, Silvio Savarese, Chen Sun, Juan Carlos Niebles

llms computer-vision nlp fine-tuning benchmarks

arXiv Machine Learning

Jul 14

Reference-Based Face Super-Resolution Using the Spatial Transformer

arXiv:2607. 11025v1 Announce Type: cross Abstract: Face super-resolution is the task of increasing the resolution of an image containing a face thereby adding finer detail.

By Varun Ramesh Jois, Antonella DiLillo, James Storer

llms computer-vision safety

arXiv AI

Jul 14

A Unified Framework for Comprehensive Cardiac CT Segmentation and Phenotyping: Human-in-the-Loop Data Annotation, Vision Foundation Model Development, Multicenter Evaluation and Clinical Validation

arXiv:2607. 11287v1 Announce Type: cross Abstract: Comprehensive quantification of cardiac structures from computed tomography (CT) remains limited not by data availability but by the scalability of measurements, which makes routine use impractical.

By Pooya Mohammadi Kazaj, Leo Fridolin Weber, Wen Xie, Seyed Amir Ahmad Safavi-Naini, Anselm Stark, Giovanni Baj, Ali Mokhtari, Toshiya Yoshida, Christoph Ryffel, Taishi Okuno, Yoshihiro Akashi, Ronny R. Buechel, Thomas Pilgrim, Waldo Valenzuela, George C. M. Siontis, Xiaowei Xu, Moritz Hundertmark, Stephan Windecker, Christoph Grani, Isaac Shiri

llms computer-vision benchmarks data-engineering

arXiv AI

Jul 14

Next-Dense-Stride Prediction for Multimodal Autoregressive Visual Modeling

arXiv:2607. 09892v1 Announce Type: cross Abstract: We introduce DenseAR, a new generative paradigm that reformulates autoregressive image generation as coarse-to-fine next-dense-stride prediction using a compact single-scale tokenizer.

By Chicago Y. Park, Jialin Mao, Xiaojian Xu, Taha Kass-Hout, Ulugbek S. Kamilov, Cao Xiao

diffusion computer-vision nlp multimodal

arXiv Machine Learning

Jul 14

DynaFilter: Cloud-driven Dynamic Filtering for Satellite Edge Intelligence

arXiv:2607. 10098v1 Announce Type: cross Abstract: Modern satellite edge systems, including those performing remote sensing tasks such object detection and tracking, are characterized by severely limited bandwidth and intermittent connections, making continuous data transmission to the cloud impractical.

By Ziyang Zhang, Jie Liu, Luca Mottola

computer-vision efficiency multimodal benchmarks

arXiv Machine Learning

Jul 14

Toward Efficient Weakly Supervised Semantic Segmentation Using Only Low-Magnification Histopathological Images

arXiv:2607. 10783v1 Announce Type: cross Abstract: Whole-slide images (WSIs) provide rich tissue-level and cellular-level information, but storing and transmitting high-magnification pathology data is resource-intensive.

By Dung Minh Do, Nhat-Thanh Huynh, Duc Minh Huynh, Doanh C. Bui, Khang Nguyen

computer-vision benchmarks

arXiv AI

Jul 14

GRC-ProbNet: Uncertainty-aware Feature Extraction for Cardiovascular Disease Classification

arXiv:2607. 10357v1 Announce Type: cross Abstract: The automatic detection and classification of cardiovascular disease (CVD) from computed tomography (CT) images plays an important role in clinical practice.

By Yash Shah, Omar Todd, Philipp Seeb\"ock, Georg Langs, Ben Glocker, Raghav Mehta

computer-vision

arXiv Machine Learning

Jul 14

Explainability Methods for Hardware Trojan Detection: A Systematic Comparison

arXiv:2601. 18696v5 Announce Type: replace Abstract: Hardware trojans are malicious circuits which compromise the functionality and security of an integrated circuit (IC).

By Paul Whitten, Francis Wolff, Chris Papachristou

computer-vision benchmarks

arXiv Machine Learning

Jul 14

An Approximate Graph Elicits Detonation Lattice

arXiv:2603. 16524v2 Announce Type: replace-cross Abstract: This study presents a novel algorithm based on graph theory for the precise segmentation and measurement of detonation cells from 3D pressure traces, termed detonation lattices, addressing the limitations of manual and primitive 2D edge detection methods prevalent in the field.

By Vansh Sharma, Venkat Raman

computer-vision