Mar 27, 2020 · Motivated by works on recurrent neural network (RNN)-based image compression and three-dimensional (3D) reconstruction, we propose unified ...
Motivated by works on recurrent neural network (RNN)-based image compression and three-dimensional (3D) reconstruction, we propose unified network architectures ...
We postulate that jointly learning these two tasks (image compression and 3D reconstruction) may lead to compression better suited for 3D reconstruction. [17] ...
Motivated by works on recurrent neural network (RNN)-based image compression and three-dimensional (3D) reconstruction, we propose unified network architectures ...
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This work introduces a method to compress 3D scenes by compressing the neural networks that represent the scenes as neural radiance fields, which provides ...
Mar 9, 2024 · Image compression optimized for 3D reconstruction by utilizing deep neural networks. Journal of visual communication and image representation, v ...
Sep 20, 2022 · I worked in the same area and saw a proposal (for h266) of using a super resolution neural network for compression (2x downscale, compress, 2x ...
Motivated by works on recurrent neural network (RNN)-based image compression and three-dimensional (3D) reconstruction, we propose unified network architectures ...
Image compression optimized for 3D reconstruction by utilizing deep neural networks ... While deep learning-based image compression methods have shown impressive ...
Article "Image compression optimized for 3D reconstruction by utilizing deep neural networks" Detailed information of the J-GLOBAL is an information service ...