most citedRepresentation-Centric Survey of Supervised Skeletal Action Recognition and the New Benchmark

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2026

GenSyn10: A Multi-Generative AI Dataset For Benchmarking Image Classification

Md Faraz Kabir Khan, Saeed Anwar, Ghulam Mubashar Hassan

The rapid advancement of generative AI has outpaced our ability to reliably detect its outputs, particularly when detectors encounter generators they have not seen before. We intro…

cs.CV20261 cited

Representation-Centric Survey of Supervised Skeletal Action Recognition and the New Benchmark

Yang Liu, Jiyao Yang, Madhawa Perera +8

3D skeletal action recognition has emerged as a powerful alternative to traditional RGB and depth-based approaches, offering robustness to environmental variations, computational e…

cs.CV2026

PointCaM: Cut-and-Mix for Open-Set Point Cloud Learning

Jie Hong, Shi Qiu, Weihao Li +4

Point cloud learning is receiving increasing attention. However, most existing point cloud models lack the practical ability to deal with the unavoidable presence of unknown object…

cs.LG2024

Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions

Zhenyue Qin, Yiqun Zhang Saeed Anwar, Dongwoo Kim +3

Most existing graph neural networks (GNNs) learn node embeddings using the framework of message passing and aggregation. Such GNNs are incapable of learning relative positions betw…

cs.CL2024

A Comprehensive Overview of Large Language Models

Humza Naveed, Asad Ullah Khan, Shi Qiu +6

Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of r…