Members in MMLab@NTU conduct research primarily in low-level vision, image and video understanding, creative content creation, 3D scene understanding and reconstruction.
Our team is the first to introduce the use of deep neural networks to directly predict super-resolved images. Our journal paper on image super-resolution was selected as the `Most Popular Article' by IEEE Transactions on Pattern Analysis and Machine Intelligence in 2016. It remains as one of the top 10 articles to date. Popular image and video super-resolution methods developed by our team include SRCNN, ESRGAN, EDVR, GLEAN and BasicVSR.
Content Editing and Generation
We research new methods for generating high-resolution, realistic and novel contents in images and videos. We are also interested in investigating fundamental concepts in generative models. Some of our works include scene deocclusion, video inpainting, image generation, and image manipulation.
Image and Video Understanding
We explore effective and efficient methods to detect, segment and recognize objects in complex scenes. We were the champion in COCO 2019 Object Detection Challenge 2019, and Open Images Challenge 2019.
3D Scene Understanding
Our team has been working on various tasks related to 3D reconstruction and perception, e.g, 3D shape generation and 3D human recovery. Check out our recent work on Variational Relational Point Completion Network, Unsupervised 3D Shape Completion through GAN Inversion and LiDAR-based Panoptic Segmentation.
We investigate new deep learning methods that are more efficient, robust, accurate, scalable, transferable, and explainable. We have been working on various problems like domain generalization, knowledge distillation, long-tailed recognition, and self-supervised learning. We participated in Facebook AI Self-Supervision Challenge 2019, and we won champions of all four tracks. Check out OpenSelfSup, our open-source project for self-supervised learning.
Anime Super-Resolution (Credit: Jan Bing)
Game Super-Resolution (Credit: Snouz)
Media Coverage | Blog
- How AI Upscaling Can Help Remaster Game Art
By Tommy Thompson in Game Developer
- Artificial Intelligence Is Helping Old Video Games Look Like New
By James Vincent in The Verge
- Meet the Upscalers
By Daniel Cooper in Engadget
- AI Neural Networks Are Giving Final Fantasy 7 a Makeover
By Fraser Brown in PC Gamer
- AI Is About to Transform The Future (And Past) of Video Games
By Aidan Moher in Input Mag
- Final Fantasy IX Recreated
By Moguri Mod