390 citations · 969 across the 10 of their papers we have counts for
10 papers
A Universal Action Space for General Behavior Analysis
Hung-Shuo Chang, Yue-Cheng Yang, Yu-Hsi Chen +6
Analyzing animal and human behavior has long been a challenging task in computer vision. Early approaches from the 1970s to the 1990s relied on hand-crafted edge detection, segment…
Deep Learning-based Animal Behavior Analysis: Insights from Mouse Chronic Pain Models
Yu-Hsi Chen, Wei-Hsin Chen, Chien-Yao Wang +3
Assessing chronic pain behavior in mice is critical for preclinical studies. However, existing methods mostly rely on manual labeling of behavioral features, and humans lack a clea…
YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary
Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Mark Liao
Identifying and localizing objects within images is a fundamental challenge, and numerous efforts have been made to enhance model accuracy by experimenting with diverse architectur…
YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems
Chien-Yao Wang, Hong-Yuan Mark Liao
This is a comprehensive review of the YOLO series of systems. Different from previous literature surveys, this review article re-examines the characteristics of the YOLO series fro…
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…
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…
NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
Yu-Hsi Chen, Chien-Yao Wang, Cheng-Yun Yang +4
We propose a post-processor, called NeighborTrack, that leverages neighbor information of the tracking target to validate and improve single-object tracking (SOT) results. It requi…
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),…
Residual Bi-Fusion Feature Pyramid Network for Accurate Single-shot Object Detection
Ping-Yang Chen, Jun-Wei Hsieh, Chien-Yao Wang +2
State-of-the-art (SoTA) models have improved the accuracy of object detection with a large margin via a FP (feature pyramid). FP is a top-down aggregation to collect semantically s…