We then present an approximate nearest neighbor search algorithm integrating the proposed ranking scheme with the product quantization-based index structure. Experimental results on the billion-level datasets demonstrate the effectiveness and superiority of the proposed method compared with several state-of-...
背景 embidding indexi 的缺点主要问题在于模型训练与索引建立的分离,导致索引建立时间增加,检索精度下降。 量化方法缺点:1)量化步骤作为基于PQ的嵌入指标的核心,具有不可微分的操作,如参数min,使标准的反向传播训练失效。因此,我们利用梯度直通估计器绕过不可微性,以实现端到端训练。2)量化质心随机初始化导致质心分配...
论文笔记-cigir21 Joint Learning of Deep Retrieval Model and Product Quantization based Embedding Index 勤劳的数据搬运工 利用数据和算法改变世界1.动机 本文核心主要通过将业界常用的OPQ压缩实现的快速检索和双塔向量化召回训练通过端到端的建模实现业务效果提升,其核心的优化逻辑点如下 通过将检索和训练的统一降低了...
image watermarkingquantization index modulationentropywavelet transformnormalization schemeTo improve the invisibility and robustness of quantization-based image watermarking algorithms, we developed an improved quantization image watermarking method based on the wavelet transform and normalization strategy used in ...
image watermarking; entropy; logarithmic quantization index modulation; generalized Gaussian distribution; wavelet transform1. Introduction With the wide application of big data and other multimedia information technology, mass multimedia data are being generated and distributed over the Internet each day. ...
The robustness is achieved by modulating the maximum SVD (Singular Value Decomposition) coefficients of image blocks by QIM (Quantization Index Modulation), and the fragile message for reversibility is embedded using histogram shifting. Compared with the other state-of-the-art schemes, our method has...
Reversible and Robust Audio Watermarking Based on Quantization Index Modulation and Amplitude ExpansionAudio codingRobustnessAcoustic signal processingInformation hidingWatermarkingExisting techniques for reversible hiding of data in audio signals are so fragile that no data can be extracted from a modified ...
CUDA 11.8pip install auto-gptq --no-build-isolation --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/2.2.1+cu118 CUDA 12.1pip install auto-gptq --no-build-isolation2.2.1+cu121 ROCm 5.7pip install auto-gptq --no-build-isolation --extra-index-url https://hugg...
CUDA 11.8pip install auto-gptq --no-build-isolation --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/2.2.1+cu118 CUDA 12.1pip install auto-gptq --no-build-isolation2.2.1+cu121 ROCm 5.7pip install auto-gptq --no-build-isolation --extra-index-url https://hugg...
Training vectors are then formed as a subset from the image data in frequency domain and is compared with a code book , to result in the index position of the code book and sent to the decoder after entropy coding . The decoder has the code book identical to the encoder and decoder ...