24 citations · 36 across the 8 of their papers we have counts for
15 papers · 1 filter
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…
LatentCRF: Continuous CRF for Efficient Latent Diffusion
Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit +5
Latent Diffusion Models (LDMs) produce high-quality, photo-realistic images, however, the latency incurred by multiple costly inference iterations can restrict their applicability.…
Less is more: Selecting informative and diverse subsets with balancing constraints
Srikumar Ramalingam, Daniel Glasner, Kaushal Patel +3
Deep learning has yielded extraordinary results in vision and natural language processing, but this achievement comes at a cost. Most models require enormous resources during train…
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…
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…
Minimal Solvers for Mini-Loop Closures in 3D Multi-Scan Alignment
Pedro Miraldo, Surojit Saha, Srikumar Ramalingam
3D scan registration is a classical, yet a highly useful problem in the context of 3D sensors such as Kinect and Velodyne. While there are several existing methods, the techniques…