RAIL-BENCH is the first standardized benchmark suite for railway perception with five challenges, real-world datasets, and a novel LineAP metric for rail track detection.
Yolo- world: Real-time open-vocabulary object detection
4 Pith papers cite this work, alongside 28 external citations. Polarity classification is still indexing.
4
Pith papers citing it
28
external citations · external index
representative citing papers
COMPASS is a manipulation-aware active sensing framework that raises simulated manipulation success rates by 24.25% over information-gain-only baselines in a new four-level confined-space benchmark.
UrbanClipAtlas integrates RAG, taxonomy-aware extraction, and video grounding into a chat interface for retrieving and interpreting events in long urban videos from street intersections.
citing papers explorer
-
Railway Artificial Intelligence Learning Benchmark (RAIL-BENCH): A Benchmark Suite for Perception in the Railway Domain
RAIL-BENCH is the first standardized benchmark suite for railway perception with five challenges, real-world datasets, and a novel LineAP metric for rail track detection.
-
COMPASS: Confined-space Manipulation Planning with Active Sensing Strategy
COMPASS is a manipulation-aware active sensing framework that raises simulated manipulation success rates by 24.25% over information-gain-only baselines in a new four-level confined-space benchmark.
-
UrbanClipAtlas: A Visual Analytics Framework for Event and Scene Retrieval in Urban Videos
UrbanClipAtlas integrates RAG, taxonomy-aware extraction, and video grounding into a chat interface for retrieving and interpreting events in long urban videos from street intersections.
- RoboAtlas: Contextual Active SLAM