GARF: Gaussian Activated Radiance Fields for High Fidelity Reconstruction and Pose Estimation

Code

• github.com/sfchng/Gaussian-Activated-Radiance-Fields
  Officialpytorch★ 113
• github.com/laura-a-n-n/tf-garf
  tf★ 0

Abstract

Despite Neural Radiance Fields (NeRF) showing compelling results in photorealistic novel views synthesis of real-world scenes, most existing approaches require accurate prior camera poses. Although approaches for jointly recovering the radiance field and camera pose exist (BARF), they rely on a cumbersome coarse-to-fine auxiliary positional embedding to ensure good performance. We present Gaussian Activated neural Radiance Fields (GARF), a new positional embedding-free neural radiance field architecture - employing Gaussian activations - that outperforms the current state-of-the-art in terms of high fidelity reconstruction and pose estimation.

Tasks

Reproductions