10.5k citations · 11.2k across the 5 of their papers we have counts for
6 papers
Designing Network Design Strategies Through Gradient Path Analysis
Chien-Yao Wang, Hong-Yuan Mark Liao, I-Hau Yeh
Designing a high-efficiency and high-quality expressive network architecture has always been the most important research topic in the field of deep learning. Most of today's networ…
SearchTrack: Multiple Object Tracking with Object-Customized Search and Motion-Aware Features
Zhong-Min Tsai, Yu-Ju Tsai, Chien-Yao Wang +3
The paper presents a new method, SearchTrack, for multiple object tracking and segmentation (MOTS). To address the association problem between detected objects, SearchTrack propose…
You Only Learn One Representation: Unified Network for Multiple Tasks
Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao
People ``understand'' the world via vision, hearing, tactile, and also the past experience. Human experience can be learned through normal learning (we call it explicit knowledge),…
Scaled-YOLOv4: Scaling Cross Stage Partial Network
Chien-Yao Wang, Alexey Bochkovskiy, Hong-Yuan Mark Liao
We show that the YOLOv4 object detection neural network based on the CSP approach, scales both up and down and is applicable to small and large networks while maintaining optimal s…
YOLOv4: Optimal Speed and Accuracy of Object Detection
Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao
There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy. Practical testing of combinations of such features on large datasets, and…
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
Chien-Yao Wang, Hong-Yuan Mark Liao, I-Hau Yeh +3
Neural networks have enabled state-of-the-art approaches to achieve incredible results on computer vision tasks such as object detection. However, such success greatly relies on co…