This repository is the implementation of"Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform"(ICCV 2021). Our code is based onCompressAI. Abstract:We propose a versatile deep image compression network based on Spatial Feature Transform (SFT), which takes a source image ...
研究点推荐 Spatially-Adaptive Feature Transform Variable-Rate Deep Image Compression Spatial Feature Transform deep image compression network 站内活动 0关于我们 百度学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们保持学习的态度,不忘初心,砥砺...
Variable rate is a requirement for flexible and adaptable image and video compression. However, deep image compression methods (DIC) are optimized for a single fixed rate-distortion (R-D) tradeoff. While this can be addressed by training multiple models for different tradeoffs, the memory requireme...
image compressionresidual codingvariable-rateRecently deep learning-based image compression has shown the potential to outperform traditional codecs. However, most existing methods train multiple networks for multiple bit rates, which increase the implementation complexity. In this paper, we propose a new...
However, in order to obtain enough bit rates to fit the performance curve, there is always a severe computational burden, especially for multispectral image compression. This problem arises not only because the complexity of the algorithm is deepening, but also repeated training with rate-distortion...
The encoder is designed to be a compression network, which compresses the high-dimensional image into a low-dimensional vector. Through this compression process, the local information of an image x is enforced to be discarded, yielding representation z that captures the global information. Then we...
Such expected characteristics, as well as the ejection velocities and event rate, are consistent with those of LRNe. After the pioneered work of [314], lots of attention has been paid to the LRNe. In particular, the properties of two LRNe in nearby galaxies (M101 OT2015-1 and M31LRN ...
where ϕ is the relative phase between the movements of the two individuals, ϕ is the derivative of ϕ with respect to time, and the ratio b/a is a control parameter corresponding to the movement rate in the experiment. An equivalent formulation of Eqn. (1) is (2)ϕ.=−∂V...
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for the image classification and segmentation, and object detection tasks. When compared to state-of-the-art post-training quantization approaches, experimental results reveal that our suggested method offers improved performance with better model compression (lower bit-rate). For per-channel quantization...