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Found 5 papers, 3 papers with code
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation
Scale-wise evaluation of object detectors is important for real-world applications.
Ranked #2 on
Small Object Detection
on SOD4SB Public Test
(using extra training data)
MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results
Small Object Detection (SOD) is an important machine vision topic because (i) a variety of real-world applications require object detection for distant objects and (ii) SOD is a challenging task due to the noisy, blurred, and less-informative image appearances of small objects.
Ranked #2 on
Small Object Detection
on SOD4SB Public Test
(using extra training data)
USB: Universal-Scale Object Detection Benchmark
To enable fair comparison and inclusive research, we propose training and evaluation protocols.
Ranked #1 on
Object Detection
on Waymo 2D detection all_ns f0val
(using extra training data)
Domain Adaptation Regularization for Spectral Pruning
We also show that our method outperforms an existing compression method studied in the DA setting by a large margin for high compression rates.
Understanding the Effects of Pre-Training for Object Detectors via Eigenspectrum
Furthermore, we propose a method for automatically determining the widths (the numbers of channels) of object detectors based on the eigenspectrum.
