5 papers
Region-Adaptive Learned Hierarchical Encoding for 3D Gaussian Splatting Data
Shashank N. Sridhara, Birendra Kathariya, Fangjun Pu +3
We introduce Region-Adaptive Learned Hierarchical Encoding (RALHE) for 3D Gaussian Splatting (3DGS) data. While 3DGS has recently become popular for novel view synthesis, the size…
Adaptive Voxelization for Transform coding of 3D Gaussian splatting data
Chenjunjie Wang, Shashank N. Sridhara, Eduardo Pavez +2
We present a novel compression framework for 3D Gaussian splatting (3DGS) data that leverages transform coding tools originally developed for point clouds. Contrary to existing 3DG…
Towards joint graph learning and sampling set selection from data
Shashank N. Sridhara, Eduardo Pavez, Antonio Ortega
We explore the problem of sampling graph signals in scenarios where the graph structure is not predefined and must be inferred from data. In this scenario, existing approaches rely…
Color-Guided Flying Pixel Correction in Depth Images
Ekamresh Vasudevan, Shashank N. Sridhara, Eduardo Pavez +3
We present a novel method to correct flying pixels within data captured by Time-of-flight (ToF) sensors. Flying pixel (FP) artifacts occur when signals from foreground and backgrou…
Graph-based Scalable Sampling of 3D Point Cloud Attributes
Shashank N. Sridhara, Eduardo Pavez, Ajinkya Jayawant +3
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 computational…