PipeMFL-240K is the first large-scale public dataset and benchmark for object detection in pipeline magnetic flux leakage images, containing 249k images and 200k annotations with long-tailed categories, tiny objects, and high intra-class variability, plus baselines showing current detectors struggle
2024.Ultralytics YOLO11
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
MuSS is a new movie-sourced dataset and benchmark that enables AI models to generate multi-shot videos with improved narrative coherence and subject identity preservation.
citing papers explorer
-
PipeMFL-240K: A Large-scale Dataset and Benchmark for Object Detection in Pipeline Magnetic Flux Leakage Imaging
PipeMFL-240K is the first large-scale public dataset and benchmark for object detection in pipeline magnetic flux leakage images, containing 249k images and 200k annotations with long-tailed categories, tiny objects, and high intra-class variability, plus baselines showing current detectors struggle
-
MuSS: A Large-Scale Dataset and Cinematic Narrative Benchmark for Multi-Shot Subject-to-Video Generation
MuSS is a new movie-sourced dataset and benchmark that enables AI models to generate multi-shot videos with improved narrative coherence and subject identity preservation.