Zobrazeno 1 - 10
of 1 491
pro vyhledávání: '"Ortega, Antonio"'
Autor:
Sridhara, Shashank N., Pavez, Eduardo, Jayawant, Ajinkya, Ortega, Antonio, Watanabe, Ryosuke, Nonaka, Keisuke
3D Point clouds (PCs) are commonly used to represent 3D scenes. They can have millions of points, making subsequent downstream tasks such as compression and streaming computationally expensive. PC sampling (selecting a subset of points) can be used t
Externí odkaz:
http://arxiv.org/abs/2410.01027
Choosing an appropriate frequency definition and norm is critical in graph signal sampling and reconstruction. Most previous works define frequencies based on the spectral properties of the graph and use the same frequency definition and $\ell_2$-nor
Externí odkaz:
http://arxiv.org/abs/2409.09526
This paper develops fast graph Fourier transform (GFT) algorithms with O(n log n) runtime complexity for rank-one updates of the path graph. We first show that several commonly-used audio and video coding transforms belong to this class of GFTs, whic
Externí odkaz:
http://arxiv.org/abs/2409.08970
We introduce a novel uncertainty principle for generalized graph signals that extends classical time-frequency and graph uncertainty principles into a unified framework. By defining joint vertex-time and spectral-frequency spreads, we quantify signal
Externí odkaz:
http://arxiv.org/abs/2409.04229
With the increasing number of images and videos consumed by computer vision algorithms, compression methods are evolving to consider both perceptual quality and performance in downstream tasks. Traditional codecs can tackle this problem by performing
Externí odkaz:
http://arxiv.org/abs/2408.07028
Autor:
Gulati, Aryan, Dong, Xingjian, Hurtado, Carlos, Shekkizhar, Sarath, Swayamdipta, Swabha, Ortega, Antonio
As language models become more general purpose, increased attention needs to be paid to detecting out-of-distribution (OOD) instances, i.e., those not belonging to any of the distributions seen during training. Existing methods for detecting OOD data
Externí odkaz:
http://arxiv.org/abs/2407.13141
Autor:
Watanabe, Ryosuke, Sridhara, Shashank N., Hong, Haoran, Pavez, Eduardo, Nonaka, Keisuke, Kobayashi, Tatsuya, Ortega, Antonio
Point clouds are a general format for representing realistic 3D objects in diverse 3D applications. Since point clouds have large data sizes, developing efficient point cloud compression methods is crucial. However, excessive compression leads to var
Externí odkaz:
http://arxiv.org/abs/2406.10520
Point clouds in 3D applications frequently experience quality degradation during processing, e.g., scanning and compression. Reliable point cloud quality assessment (PCQA) is important for developing compression algorithms with good bitrate-quality t
Externí odkaz:
http://arxiv.org/abs/2406.09762
Current video coding standards, including H.264/AVC, HEVC, and VVC, employ discrete cosine transform (DCT), discrete sine transform (DST), and secondary to Karhunen-Loeve transforms (KLTs) decorrelate the intra-prediction residuals. However, the effi
Externí odkaz:
http://arxiv.org/abs/2402.16371
This paper proposes a compression framework for adjacency matrices of weighted graphs based on graph filter banks. Adjacency matrices are widely used mathematical representations of graphs and are used in various applications in signal processing, ma
Externí odkaz:
http://arxiv.org/abs/2402.02884