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computer vision

4,009 papers

#artificial intelligence Preprint Sep 2026

ERPBench: A State-Grounded Evaluation Paradigm for Computer-Use Agents in Enterprise Software

ERPBench is introduced, a benchmark that evaluates screenshot-only agents on a live and reproducible system and scores each task against ground-truth values in its database and presents a production-grade harness that gates agent actions behind human approval for safe deployment.

Kratika Bhagtani, K. Sridhar, M. B. Pouyan et al. · 1 citation
#artificial intelligence Preprint Open access Sep 2026

Graph Neural Assisted Actor-Critic for Latency-Efficient Edge Vision System

UAV on-board vision systems are widely used for different activities, including monitoring in no-fly zones. In this case, the vision-equipped UAV streams a video to a ground server where an operator assists its activities. The latency of video transmission has a profound impact on the effectiveness of the operator assi...

Alam Noor, Luis Almeida, Kai Li et al. · 0 citations

RoofSeg: An edge-aware transformer-based network for end-to-end roof plane segmentation

A novel edge-aware transformer-based network, named RoofSeg, is developed for segmenting roof planes from LiDAR point clouds in a truly end-to-end manner and an Edge-Aware Mask Module (EAMM) is designed that sufficiently incorporates planar geometric prior of edges to enhance its discriminability for plane instance mas...

Si-Yuan You, Guo-Zheng Xu, Peng-Wei Zhou et al. · 0 citations

CLIP Embeddings for AI-Generated Image Detection: A Few-Shot Study with Lightweight Classifier

This work investigates whether CLIP embeddings inherently contain information indicative of AI generation, and proposes a proposed pipeline that extracts visual embeddings using a frozen CLIP model, feeds its embeddings to lightweight networks, and fine-tunes only the final classifier.

Zi-Yang Ou · 2 citations

Same Answer, Different Representations: Hidden instability in VLMs

A representation-aware and frequency-aware evaluation framework that measures internal embedding drift, spectral sensitivity, and structural smoothness (spatial consistency of vision tokens), alongside standard label-based metrics is introduced.

Farooq Ahmad Wani, Alessandro Suglia, Rohit Saxena et al. · 2 citations
#artificial intelligence Preprint Sep 2026

PhysStream: Streaming Physics-Grounded Video Generation with Structured Scene Memory and Fine-Grained Motion Control

PhysStream is an autoregressive model for physics-grounded image-to-video synthesis that incorporates structured scene memory and supports fine-grained motion control via sparse velocity-increment signals that encode physical quantities, letting the model learn the underlying dynamics.

Chuhao Chen, Peter Wonka, Chao-Yang Wang et al. · 2 citations
#artificial intelligence Open access Sep 2026

Det‐ LIME : Detector‐Aware, Multi‐Instance Local Interpretable Model‐Agnostic Explanations for Automated Marine Mammal Detection

Det‐LIME is proposed, a detector‐aware, multi‐instance adaptation of Local Interpretable Model Agnostic Explanations that produced instance‐specific, box‐aligned explanations by combining per‐detection weighting, a proximity kernel that emphasizes regions near each box, and Intersection‐over‐Union‐based matching to tra...

Jia-Yi Zhou, David W. Johnston, Brinnae Bent · 0 citations
#artificial intelligence Preprint Sep 2026

Tracking the Unseen: An Occlusion-Robust Framework for Target Tracking Under Full and Long-Term Occlusion

An occlusion-robust target tracking framework that maintains target identity and trajectory continuity through the integration of YOLOv11n object detection, Kalman Filter motion prediction, and occlusion-aware appearance-based re-identification is proposed.

Mais.M Mohammed, Sharifa Mohammed, Hanan Awadh et al. · 0 citations
#artificial intelligence Preprint Sep 2026

FROD: Feature Matching Residual Denoising Oracle Bone Decipher

This work forms OBS decipherment assistance as a cross-era image translation task and proposes FROD (Feature Matching Residual Denoising Oracle Bone Decipher), a Residual Denoising Diffusion Model that jointly estimates noise and residual signals, thereby reducing the positional drift and stroke disorder commonly obser...

Yan-Bin Hou, Biao Xiong, Guo-Jun Xu et al. · 0 citations
#artificial intelligence Preprint Open access Sep 2026

Multimodal Cultural Heritage Architectural Style Classification for Residential Buildings in the UAE Based on CLIP Embeddings and SVM

The analysis and classification of cultural heritage architectural styles remain challenging due to the complexity of visual images of buildings, which are highly relied on in traditional CNN-based classification approaches in comparison to textual descriptions, and the relative lack of non-western region-specific data...

Ahmed Ammar Kubba, Manar Abu Talib, Iman Ibrahim et al. · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

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.

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