20 citations · 23 across the 5 of their papers we have counts for
5 papers
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation
Yosuke Shinya
Scale-wise evaluation of object detectors is important for real-world applications. However, existing metrics are either coarse or not sufficiently reliable. In this paper, we prop…
MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results
Yuki Kondo, Norimichi Ukita, Takayuki Yamaguchi +19
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 ch…
USB: Universal-Scale Object Detection Benchmark
Yosuke Shinya
Benchmarks, such as COCO, play a crucial role in object detection. However, existing benchmarks are insufficient in scale variation, and their protocols are inadequate for fair com…
Domain Adaptation Regularization for Spectral Pruning
Laurent Dillard, Yosuke Shinya, Taiji Suzuki
Deep Neural Networks (DNNs) have recently been achieving state-of-the-art performance on a variety of computer vision related tasks. However, their computational cost limits their…
Understanding the Effects of Pre-Training for Object Detectors via Eigenspectrum
Yosuke Shinya, Edgar Simo-Serra, Taiji Suzuki
ImageNet pre-training has been regarded as essential for training accurate object detectors for a long time. Recently, it has been shown that object detectors trained from randomly…