Video super-resolution based on deep learning: a comprehensive survey

H Liu, Z Ruan, P Zhao, C Dong, F Shang, Y Liu… - Artificial Intelligence …, 2022 - Springer
Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution
ones. Recently, the VSR methods based on deep neural networks have made great …

Generative adversarial networks for spatio-temporal data: A survey

N Gao, H Xue, W Shao, S Zhao, KK Qin… - ACM Transactions on …, 2022 - dl.acm.org
Generative Adversarial Networks (GANs) have shown remarkable success in producing
realistic-looking images in the computer vision area. Recently, GAN-based techniques are …

Alias-free generative adversarial networks

T Karras, M Aittala, S Laine… - Advances in neural …, 2021 - proceedings.neurips.cc
We observe that despite their hierarchical convolutional nature, the synthesis process of
typical generative adversarial networks depends on absolute pixel coordinates in an …

Id-animator: Zero-shot identity-preserving human video generation

X He, Q Liu, S Qian, X Wang, T Hu, K Cao… - arxiv preprint arxiv …, 2024 - arxiv.org
Generating high-fidelity human video with specified identities has attracted significant
attention in the content generation community. However, existing techniques struggle to …

Physics-informed computer vision: A review and perspectives

C Banerjee, K Nguyen, C Fookes, K George - ACM Computing Surveys, 2024 - dl.acm.org
The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …

[PDF][PDF] Detecting Deepfake Videos with Temporal Dropout 3DCNN.

D Zhang, C Li, F Lin, D Zeng, S Ge - IJCAI, 2021 - ijcai.org
While the abuse of deepfake technology has brought about a serious impact on human
society, the detection of deepfake videos is still very challenging due to their highly …