434 citations · 1.3k across the 60 of their papers we have counts for
13 papers · 1 filter
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
Benjamin Kiefer, Matej Kristan, Janez Perš +70
The 1 Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and…
HuPR: A Benchmark for Human Pose Estimation Using Millimeter Wave Radar
Shih-Po Lee, Niraj Prakash Kini, Wen-Hsiao Peng +2
This paper introduces a novel human pose estimation benchmark, Human Pose with Millimeter Wave Radar (HuPR), that includes synchronized vision and radio signal components. This dat…
Image-Text Retrieval with Binary and Continuous Label Supervision
Zheng Li, Caili Guo, Zerun Feng +3
Most image-text retrieval work adopts binary labels indicating whether a pair of image and text matches or not. Such a binary indicator covers only a limited subset of image-text s…
Observation Centric and Central Distance Recovery on Sports Player Tracking
Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang +3
Multi-Object Tracking over humans has improved rapidly with the development of object detection and re-identification. However, multi-actor tracking over humans with similar appear…
Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval
Zheng Li, Caili Guo, Xin Wang +3
There are two popular loss functions used for vision-language retrieval, i.e., triplet loss and contrastive learning loss, both of them essentially minimize the difference between…
GaitTAKE: Gait Recognition by Temporal Attention and Keypoint-guided Embedding
Hung-Min Hsu, Yizhou Wang, Cheng-Yen Yang +3
Gait recognition, which refers to the recognition or identification of a person based on their body shape and walking styles, derived from video data captured from a distance, is w…
GLIPv2: Unifying Localization and Vision-Language Understanding
Haotian Zhang, Pengchuan Zhang, Xiaowei Hu +7
We present GLIPv2, a grounded VL understanding model, that serves both localization tasks (e.g., object detection, instance segmentation) and Vision-Language (VL) understanding tas…
Unsupervised Domain Adaptation Learning for Hierarchical Infant Pose Recognition with Synthetic Data
Cheng-Yen Yang, Zhongyu Jiang, Shih-Yu Gu +2
The Alberta Infant Motor Scale (AIMS) is a well-known assessment scheme that evaluates the gross motor development of infants by recording the number of specific poses achieved. Wi…
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey
Gaoang Wang, Mingli Song, Jenq-Neng Hwang
Multi-object tracking (MOT) aims to associate target objects across video frames in order to obtain entire moving trajectories. With the advancement of deep neural networks and the…
TR-MOT: Multi-Object Tracking by Reference
Mingfei Chen, Yue Liao, Si Liu +2
Multi-object Tracking (MOT) generally can be split into two sub-tasks, i.e., detection and association. Many previous methods follow the tracking by detection paradigm, which first…
The Overlooked Classifier in Human-Object Interaction Recognition
Ying Jin, Yinpeng Chen, Lijuan Wang +5
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image. This paper shows…
HCIL: Hierarchical Class Incremental Learning for Longline Fishing Visual Monitoring
Jie Mei, Suzanne Romain, Craig Rose +2
The goal of electronic monitoring of longline fishing is to visually monitor the fish catching activities on fishing vessels based on cameras, either for regulatory compliance or c…
Unsupervised Severely Deformed Mesh Reconstruction (DMR) from a Single-View Image
Jie Mei, Jingxi Yu, Suzanne Romain +4
Much progress has been made in the supervised learning of 3D reconstruction of rigid objects from multi-view images or a video. However, it is more challenging to reconstruct sever…