Aim 2
AIM (presumably an acronym for a research initiative or challenge) focuses on advancing various computer vision and machine learning tasks, primarily through efficient model design and improved data utilization. Current research emphasizes developing real-time, resource-efficient solutions for video super-resolution, depth map processing, and image quality assessment, often leveraging neural networks and techniques like knowledge distillation and low-precision inference. These advancements have significant implications for applications ranging from augmented and virtual reality to mobile photography and video streaming, improving both the quality and accessibility of these technologies.
Papers
Compressed Depth Map Super-Resolution and Restoration: AIM 2024 Challenge Results
Marcos V. Conde, Florin-Alexandru Vasluianu, Jinhui Xiong, Wei Ye, Rakesh Ranjan, Radu Timofte
AIM 2024 Challenge on UHD Blind Photo Quality Assessment
Vlad Hosu, Marcos V. Conde, Lorenzo Agnolucci, Nabajeet Barman, Saman Zadtootaghaj, Radu Timofte
AIM 2024 Sparse Neural Rendering Challenge: Dataset and Benchmark
Michal Nazarczuk, Thomas Tanay, Sibi Catley-Chandar, Richard Shaw, Radu Timofte, Eduardo Pérez-Pellitero
AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Dmitry Vatolin, Radu Timofte, Gen Zhan, Li Yang, Yunlong Tang, Yiting Liao, Jiongzhi Lin, Baitao Huang, Morteza Moradi, Mohammad Moradi, Francesco Rundo, Concetto Spampinato, Ali Borji, Simone Palazzo, Yuxin Zhu, Yinan Sun, Huiyu Duan, Yuqin Cao, Ziheng Jia, Qiang Hu, Xiongkuo Min, Guangtao Zhai, Hao Fang, Runmin Cong, Xiankai Lu, Xiaofei Zhou, Wei Zhang, Chunyu Zhao, Wentao Mu, Tao Deng, Hamed R. Tavakoli
Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile AI & AIM 2022 challenge: Report
Andrey Ignatov, Radu Timofte, Jin Zhang, Feng Zhang, Gaocheng Yu, Zhe Ma, Hongbin Wang, Minsu Kwon, Haotian Qian, Wentao Tong, Pan Mu, Ziping Wang, Guangjing Yan, Brian Lee, Lei Fei, Huaijin Chen, Hyebin Cho, Byeongjun Kwon, Munchurl Kim, Mingyang Qian, Huixin Ma, Yanan Li, Xiaotao Wang, Lei Lei
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report
Andrey Ignatov, Grigory Malivenko, Radu Timofte, Lukasz Treszczotko, Xin Chang, Piotr Ksiazek, Michal Lopuszynski, Maciej Pioro, Rafal Rudnicki, Maciej Smyl, Yujie Ma, Zhenyu Li, Zehui Chen, Jialei Xu, Xianming Liu, Junjun Jiang, XueChao Shi, Difan Xu, Yanan Li, Xiaotao Wang, Lei Lei, Ziyu Zhang, Yicheng Wang, Zilong Huang, Guozhong Luo, Gang Yu, Bin Fu, Jiaqi Li, Yiran Wang, Zihao Huang, Zhiguo Cao, Marcos V. Conde, Denis Sapozhnikov, Byeong Hyun Lee, Dongwon Park, Seongmin Hong, Joonhee Lee, Seunggyu Lee, Se Young Chun