63 citations · 148 across the 22 of their papers we have counts for
23 papers
Two-Stream temporal transformer for video action classification
Nattapong Kurpukdee, Adrian G. Bors
Motion representation plays an important role in video understanding and has many applications including action recognition, robot and autonomous guidance or others. Lately, transf…
Unsupervised Video Class-Incremental Learning via Deep Embedded Clustering Management
Nattapong Kurpukdee, Adrian G. Bors
Unsupervised video class incremental learning (uVCIL) represents an important learning paradigm for learning video information without forgetting, and without considering any data…
Inference-based GAN Video Generation
Jingbo Yang, Adrian G. Bors
Video generation has seen remarkable progress thanks to advancements in generative deep learning. However, generating long sequences remains a significant challenge. Generated vide…
Unsupervised Video Continual Learning via Non-Parametric Deep Embedded Clustering
Nattapong Kurpukdee, Adrian G. Bors
We propose a realistic scenario for the unsupervised video learning where neither task boundaries nor labels are provided when learning a succession of tasks. We also provide a non…
Masked Image Residual Learning for Scaling Deeper Vision Transformers
Guoxi Huang, Hongtao Fu, Adrian G. Bors
Deeper Vision Transformers (ViTs) are more challenging to train. We expose a degradation problem in deeper layers of ViT when using masked image modeling (MIM) for pre-training. To…
Dynamic Appearance: A Video Representation for Action Recognition with Joint Training
Guoxi Huang, Adrian G. Bors
Static appearance of video may impede the ability of a deep neural network to learn motion-relevant features in video action recognition. In this paper, we introduce a new concept,…