When applying a pre-trained 2D-to-3D Human Pose lifting model to a target unseen dataset,
a large performance degradation is commonly encountered due to domain shift issues. We …

Deep learning-based object detectors have driven notable progress in multi-object tracking
algorithms. Yet, current tracking methods mainly focus on simple, regular motion patterns in …

In the field of multi-object tracking (MOT), traditional methods often rely on the Kalman Filter
for motion prediction, leveraging its strengths in linear motion scenarios. However, the …

Recent integration of Natural Language Processing (NLP) and multimodal models has
advanced the field of sports analytics. This survey presents a comprehensive review of the …

In recent times, there has been a growing interest in developing effective perception
techniques for combining information from multiple modalities. This involves aligning …

Although 3D human pose estimation has gained impressive development in recent years,
only a few works focus on infants, that have different bone lengths and also have limited …

In football or soccer, a referee controls the game based on the set rules. The decisions made
by the referee are final and can't be appealed. Some of the decisions, especially after a …

We present a transformer decoder based model, SportsNGEN, that is trained on sports
player and ball tracking sequences that is capable of generating realistic and sustained …

近年來, 將體育賽事與深度學習架構相結合在應用層面引起了廣泛地關注, 其中智能裁判,
戰術規劃等結合神經網路進行輔助之需求日漸增加. 在相關的應用當中, 深度學習架構通常扮演 …

Athlete monitoring is essential for improving training, preventing injuries, and enhancing
performance. With the advancement of wearable sensors and artificial intelligence (AI) …