43 citations · 52 across the 10 of their papers we have counts for
10 papers
PL-NBA: A Possession-level Universal Basketball Video Dataset Supporting Multiple Visual Understanding Tasks
Yunhao Zhao, Haoying Sun, Jiarui Li +5
Visual understanding in sports has emerged as a hot topic in computer vision in recent years. Most existing basketball video datasets adopt single action or activity as sample, whi…
NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams
Lifang Wu, Yuyang Wu, Yangdong Gao +3
Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. However, existing methods are…
Player-Centric Multimodal Prompt Generation for Large Language Model Based Identity-Aware Basketball Video Captioning
Zeyu Xi, Haoying Sun, Yaofei Wu +5
Existing sports video captioning methods often focus on the action yet overlook player identities, limiting their applicability. Although some methods integrate extra information t…
VicKAM: Visual Conceptual Knowledge Guided Action Map for Weakly Supervised Group Activity Recognition
Zhuming Wang, Yihao Zheng, Jiarui Li +5
Existing weakly supervised group activity recognition methods rely on object detectors or attention mechanisms to capture key areas automatically. However, they overlook the semant…
Knowledge Guided Entity-aware Video Captioning and A Basketball Benchmark
Zeyu Xi, Ge Shi, Xuefen Li +5
Despite the recent emergence of video captioning models, how to generate the text description with specific entity names and fine-grained actions is far from being solved, which ho…
Knowledge Augmented Relation Inference for Group Activity Recognition
Xianglong Lang, Zhuming Wang, Zun Li +4
Most existing group activity recognition methods construct spatial-temporal relations merely based on visual representation. Some methods introduce extra knowledge, such as action…
Learning to Compose Diversified Prompts for Image Emotion Classification
Sinuo Deng, Lifang Wu, Ge Shi +3
Contrastive Language-Image Pre-training (CLIP) represents the latest incarnation of pre-trained vision-language models. Although CLIP has recently shown its superior power on a wid…
Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos
Lifang Wu, Zhou Yang, Qi Wang +4
Many semantic events in team sport activities e.g. basketball often involve both group activities and the outcome (score or not). Motion patterns can be an effective means to ident…
LFFD: A Light and Fast Face Detector for Edge Devices
Yonghao He, Dezhong Xu, Lifang Wu +3
Face detection, as a fundamental technology for various applications, is always deployed on edge devices which have limited memory storage and low computing power. This paper intro…
Ontology Based Global and Collective Motion Patterns for Event Classification in Basketball Videos
Lifang Wu, Zhou Yang, Jiaoyu He +4
In multi-person videos, especially team sport videos, a semantic event is usually represented as a confrontation between two teams of players, which can be represented as collectiv…