Multi-Indexed Convolution introduces an alternative approach to spatial feature extraction, which we use in our entropy model to compress the occupation symbols of octree-encoded point clouds. This method offers reduc...
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This paper proposes a method that enhances the compression performance of the current model under development for the upcoming MPEG standard on Feature compression for Machines (FCM) [1]. By truncating low-activation ...
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We compare in this work the robustness of machine learning based image compression algorithms with classical algorithms such as JPEG. For this, we run adversarial attacks against [2] and [1] as two examples for the fi...
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For the archiving of mammograms, the FDA requires lossless image compression. Using near-lossless compressors for temporary examination of medical images could be advantageous 'if the interpreting physician deems ...
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The widespread adoption of smartphones with high-resolution cameras has driven a surge in image capture, particularly for selfies, food, and landscapes, which dominate social media. Efficient image compression is esse...
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Palindromes are sequences of characters that read the same forward and backward and have fascinated computer scientists for centuries due to their unique properties. The exploration of palindromes sheds light on funda...
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In this paper, we address the limitations of current measures for estimating the lossless compression limits. Shannon entropy, while practical, assumes a known data distribution and does not account for the complexity...
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We present two adaptive coding methods that perform especially well on large alphabets like those used in word-level text compression. The first is based on re-indexing a universal codeword set. The more evolved secon...
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We propose ICE, an efficient and intelligent system that utilizes our dual-algorithm strategy to achieve superior lossless block-level compression results compared to traditional single compressor methods, especially ...
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This paper investigates the impact of standardized Geometry-based Point Cloud compression (G-PCC) on LiDAR-based object detection tasks. It evaluates how compression distortion types, and distortion levels, together w...
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