这个论文引入 VQGAN 的思想进行图像修复。作者认为,现有的夜间图像恢复方法效果不好是因为缺乏稳定和可靠的先验知识。为了解决这个问题,论文引入了向量量化(VQ)代码簿作为一个可靠和高质量的外部特征库,为纯数据驱动的图像恢复提供高质量先验。 同时,做了两个改进,提出了自适应光照增强模块(AIEM)和可变形双向交叉注意力(DBCA)模块来确
importvector_quantize_pytorchasvqimporttorcha=torch.FloatTensor([-0.1,0.5,0.2,0.33,-0.6,0.2]).view(1,3,2)print('a=',a)quantizer=vq.VectorQuantize(dim=2,codebook_size=6)quantized,indices,loss=quantizer(a)print('quantized',quantized)print('indices',indices)print('loss',loss) 输入为一个三维...
not available for EP107497of corresponding document:In a CELP type speech coder, the excitation is quantized by vectors from a random codebook. The random codebook is made of a fixed waveform storage section (181), followed by a vector rearranging unit (182). The rearranging section (182) ...
研究方向 |NLP、神经网络 无独有偶,近期发布在 arXiv 上的论文《Addressing Representation Collapse in Vector Quantized Models with One Linear Layer》[1]提出了改善 VQ 的另一个技巧:给编码表加一个线性变换。这个技巧单纯改变了编码表的参数化方式,不改变 VQ 背后的理论框架,但实测效果非常优异,称得上是简单有...
main BranchesTags Code Folders and files Name Last commit message Last commit date Latest commit History 8 Commits Figures models utils README.md inference_vqlol.py test_metric.py README This is the office implementation ofVQCNIR: Clearer Night Image Restoration with Vector-Quantized Codebook, AAAI...
Assuming that the stream x is the input to a quantizer, then the corresponding values from the output stream y are obtained by a reference to the quantizer codebook. According to Shannon (1948), the amount of uncertainty R(x,y) of a value of x when we receive its quantized counterpart ...
quantized=self.maybe_l2norm(quantized) 302303 303304 # use straight-through gradients (optionally with custom activation fn) if training 304305 @@ -313,8 +314,7 @@ def forward( 313314 ifself.training: 314315 codebook=self.codebook 315316 ...
quantized using a non-uniform scalar codebook with a proper transformation function, while the direction of the latent vector is quantized using a trainable Grassmannian codebook. A multi-rate codebook design strategy is also developed by introducing a codeword selection rule for a nested codebook ...
Is it necessary for autoregressive models to be coupled with vector-quantized representations? 毕竟大伙有目共睹,VQ tokenizer 是真的难训,其中 quantized vector 的采样(从 codebook 中)是不可导的,于是通常采用 straight-through 这样的梯度估计方法将 quantized vector 的梯度(来自 Decoder)直接复制给 encoder ...
A sequence of data, pixels, audio samples or sensor data is often quantized by treating each datum independently. This is referred to as scalar quantization. VQ, on the other hand, quantizes blocks or vectors of data. A primary issue with VQ is the need to find a set of representative ...