activity
20182025
most citedSSDNeRF: Semantic Soft Decomposition of Neural Radiance Fields

5 citations · 6 across the 3 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

SurfR: Surface Reconstruction with Multi-scale Attention

Siddhant Ranade, Gonçalo Dias Pais, Ross Tyler Whitaker +3

We propose a fast and accurate surface reconstruction algorithm for unorganized point clouds using an implicit representation. Recent learning methods are either single-object repr…

cs.CV20225 cited

SSDNeRF: Semantic Soft Decomposition of Neural Radiance Fields

Siddhant Ranade, Christoph Lassner, Kai Li +4

Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function. This is achieved by using an MLP together with a mapping to a higher-…

cs.CV2020

Mapping of Sparse 3D Data using Alternating Projection

Siddhant Ranade, Xin Yu, Shantnu Kakkar +2

We propose a novel technique to register sparse 3D scans in the absence of texture. While existing methods such as KinectFusion or Iterative Closest Points (ICP) heavily rely on de…

cs.CV2020

PoseNet3D: Learning Temporally Consistent 3D Human Pose via Knowledge Distillation

Shashank Tripathi, Siddhant Ranade, Ambrish Tyagi +1

Recovering 3D human pose from 2D joints is a highly unconstrained problem. We propose a novel neural network framework, PoseNet3D, that takes 2D joints as input and outputs 3D skel…

cs.CV20191 cited

Can generalised relative pose estimation solve sparse 3D registration?

Siddhant Ranade, Xin Yu, Shantnu Kakkar +2

Popular 3D scan registration projects, such as Stanford digital Michelangelo or KinectFusion, exploit the high-resolution sensor data for scan alignment. It is particularly challen…

cs.CV2018

Learning Material-Aware Local Descriptors for 3D Shapes

Hubert Lin, Melinos Averkiou, Evangelos Kalogerakis +5

Material understanding is critical for design, geometric modeling, and analysis of functional objects. We enable material-aware 3D shape analysis by employing a projective convolut…