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
Results support the effectiveness of caption memory for episodic reasoning over long egocentric video in wearable assistants with bounded frame budgets, growing visual-token costs, and long-context retrieval failures.
Dingli Liang, Yi Xie, Yu-Kai Huang et al.· 0 citations
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
T2T-VICL, a collaborative prompt-transfer framework, which converts mismatched visual demonstrations into implicit textual guidance without explicitly naming the tasks, is proposed.
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.· Isprs Journal of Photogramme...· 0 citations
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.
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.· arXiv.org· 2 citations
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
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· Marine mammal science· 0 citations
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
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
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
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
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.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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