most citedAdaptive sampling for scanning pixel cameras

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cs.CV2024

HyperGS: Hyperspectral 3D Gaussian Splatting

Christopher Thirgood, Oscar Mendez, Erin Chao Ling +2

We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneo…

cs.CV2024

PEnG: Pose-Enhanced Geo-Localisation

Tavis Shore, Oscar Mendez, Simon Hadfield

Cross-view Geo-localisation is typically performed at a coarse granularity, because densely sampled satellite image patches overlap heavily. This heavy overlap would make disambigu…

cs.CV2024

Single-image coherent reconstruction of objects and humans

Sarthak Batra, Partha P. Chakrabarti, Simon Hadfield +1

Existing methods for reconstructing objects and humans from a monocular image suffer from severe mesh collisions and performance limitations for interacting occluding objects. This…

cs.CV2024

The Third Monocular Depth Estimation Challenge

Jaime Spencer, Fabio Tosi, Matteo Poggi +38

This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-…

cs.CV2024

S3R-Net: A Single-Stage Approach to Self-Supervised Shadow Removal

Nikolina Kubiak, Armin Mustafa, Graeme Phillipson +2

In this paper we present S3R-Net, the Self-Supervised Shadow Removal Network. The two-branch WGAN model achieves self-supervision relying on the unify-and-adaptphenomenon - it unif…

cs.CV2024

Kick Back & Relax++: Scaling Beyond Ground-Truth Depth with SlowTV & CribsTV

Jaime Spencer, Chris Russell, Simon Hadfield +1

Self-supervised learning is the key to unlocking generic computer vision systems. By eliminating the reliance on ground-truth annotations, it allows scaling to much larger data qua…