Understanding Deformable Alignment in Video Super-Resolution

Authors: Kelvin C.K. Chan, Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy973-981

AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We further demonstrate through experiments that the increased diversity in deformable alignment yields better-aligned features, and hence significantly improves the quality of video super-resolution output. Experiments show that our loss successfully avoids the overflow of offsets and alleviates the instability problem of deformable alignment. We conduct experiments to reveal the connections and differences between deformable and flow-based alignments in video SR.
Researcher Affiliation Collaboration 1S-Lab, Nanyang Technological University 2Applied Research Center, Tencent PCG 3CUHK Sense Time Joint Lab, The Chinese University of Hong Kong 4Shenzhen Key Lab of Computer Vision and Pattern Recognition, SIAT-Sense Time Joint Lab, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences 5SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society
Pseudocode No The paper does not contain any clearly labeled pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any explicit statement about releasing source code or a link to a code repository for the described methodology.
Open Datasets Yes Table 3: Quantitative comparison (PSNR) on REDS4 and Vimeo-90K-T for 4 video super-resolution.
Dataset Splits No The paper mentions using specific datasets (REDS4, Vimeo-90K-T) but does not explicitly detail the training, validation, or test splits within the main text, deferring these to supplementary material.
Hardware Specification No The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used to run the experiments.
Software Dependencies No The paper does not list specific software dependencies with version numbers necessary for reproducibility.
Experiment Setup Yes The quantities are robust to changes, and λ=1, t=10 is a reasonable setting.