849 citations · 1.2k across the 4 of their papers we have counts for
4 papers
YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao
Today's deep learning methods focus on how to design the most appropriate objective functions so that the prediction results of the model can be closest to the ground truth. Meanwh…
YOLOR-Based Multi-Task Learning
Hung-Shuo Chang, Chien-Yao Wang, Richard Robert Wang +2
Multi-task learning (MTL) aims to learn multiple tasks using a single model and jointly improve all of them assuming generalization and shared semantics. Reducing conflicts between…
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…
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Chien-Yao Wang, Alexey Bochkovskiy, Hong-Yuan Mark Liao
YOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all known real-time object det…