arXiv AI July 21, 2026 By Anshu Singh, Alejandro Seif

Privacy-Aware Synthetic Video Benchmarking and Relational Evaluation for Worker-Under-Suspended-Load Detection

arXiv:2607. 16351v1 Announce Type: cross Abstract: Publicly shareable construction-video benchmarks remain scarce, especially for safety-critical hazards that are rare, dangerous to stage, and difficult to release.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Computer Vision

Aug 24

Cloak of Invisibility: Real-Time Privacy-Preserving Volumetric Video Streaming

arXiv:2608.11645v2 Announce Type: replace Abstract: Volumetric video streaming turns privacy into a 3D, multi-view problem. Unlike ordinary video, where sensitive content can often be redacted frame...

By Hossein Khalili (UCLA), Philip Do (UCLA), Alexander Vilesov (UCLA), Achuta Kadambi (UCLA), Kittipat Apicharttrisorn (Nokia Bell Labs), Nader Sehatbakhsh (UCLA)

computer-vision safety

arXiv AI

Aug 6

Robust and Efficient Motion Reasoning for Privacy-Aware Classroom Incident Recognition

arXiv:2608. 05115v1 Announce Type: cross Abstract: Can computer vision help make classrooms safer?

By Paritosh Parmar, Landy Lan, Hong Yang, Chen Yi, Chiat Pin Tay

computer-vision benchmarks safety

Hugging Face Trending Papers

Jul 6

SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments

Existing video benchmarks evaluate action recognition on consumer videos, egocentric recordings, or simulated industrial environments. They do not test vision-language models under the visual and procedural conditions of real industrial CCTV, where workers appear as distant figures amid dust, steam, low light, glare, occlusion, and overlapping activities.

llms multimodal benchmarks safety

arXiv AI

Sep 1

Defending Wearable VLMs Against Private Attribute Inference

arXiv:2608.28691v1 Announce Type: cross Abstract: Wearable VLM pipelines promise continuous multimodal assistance from egocentric visual capture: a user asks a task-driven question about the surround...

By Zhimin Li, Pan Wang, Jingxian Chen, Yuantao Tang, Anthony Chen, Qian Lou, Jingtong Hu

llms multimodal benchmarks safety

arXiv Computer Vision

4d ago

From Laboratory to Real World: A New Benchmark Towards Privacy-Preserved Visible-Infrared Person Re-Identification

arXiv:2503.12232v3 Announce Type: replace Abstract: Aiming to match pedestrian images captured under varying lighting conditions, visible-infrared person re-identification (VI-ReID) has drawn intensi...

By Yan Jiang, Hao Yu, Xu Cheng, Haoyu Chen, Zhaodong Sun, Guoying Zhao

benchmarks safety

arXiv AI

Aug 18

Privacy-Preserving Dataset Curation for Kuala Lumpur Urban Traffic: Grounded Vision-Language Detection with Spatial Vehicle-Context Filtering

arXiv:2608. 14724v1 Announce Type: cross Abstract: The rapid advancement of intelligent transportation systems and autonomous driving relies heavily on multi-modal urban traffic datasets.

By Mohammed Abdul Al Arafat Tanzin, Rudzidatul Akmam Dziyauddin

llms agents robotics multimodal safety

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Related stories

Cloak of Invisibility: Real-Time Privacy-Preserving Volumetric Video Streaming

Robust and Efficient Motion Reasoning for Privacy-Aware Classroom Incident Recognition

SteelBench: Evaluating Vision-Language Models in Real-World Industrial Environments

Defending Wearable VLMs Against Private Attribute Inference

From Laboratory to Real World: A New Benchmark Towards Privacy-Preserved Visible-Infrared Person Re-Identification

Privacy-Preserving Dataset Curation for Kuala Lumpur Urban Traffic: Grounded Vision-Language Detection with Spatial Vehicle-Context Filtering