15 citations · 33 across the 4 of their papers we have counts for
7 papers
Curvature-Aware Training for Coordinate Networks
Hemanth Saratchandran, Shin-Fang Chng, Sameera Ramasinghe +2
Coordinate networks are widely used in computer vision due to their ability to represent signals as compressed, continuous entities. However, training these networks with first-ord…
On Quantizing Implicit Neural Representations
Cameron Gordon, Shin-Fang Chng, Lachlan MacDonald +1
The role of quantization within implicit/coordinate neural networks is still not fully understood. We note that using a canonical fixed quantization scheme during training produces…
GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation
Shin-Fang Chng, Sameera Ramasinghe, Jamie Sherrah +1
Despite Neural Radiance Fields (NeRF) showing compelling results in photorealistic novel views synthesis of real-world scenes, most existing approaches require accurate prior camer…
Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging
Álvaro Parra, Shin-Fang Chng, Tat-Jun Chin +2
Under mild conditions on the noise level of the measurements, rotation averaging satisfies strong duality, which enables global solutions to be obtained via semidefinite programmin…
Quantum Robust Fitting
Tat-Jun Chin, David Suter, Shin-Fang Chng +1
Many computer vision applications need to recover structure from imperfect measurements of the real world. The task is often solved by robustly fitting a geometric model onto noisy…
Resolving Marker Pose Ambiguity by Robust Rotation Averaging with Clique Constraints
Shin-Fang Ch'ng, Naoya Sogi, Pulak Purkait +2
Planar markers are useful in robotics and computer vision for mapping and localisation. Given a detected marker in an image, a frequent task is to estimate the 6DOF pose of the mar…