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GSta: Efficient Training Scheme with Siestaed Gaussians for Monocular 3D Scene Reconstruction
Anil Armagan, Albert Saà-Garriga, Bruno Manganelli +2
Gaussian Splatting (GS) is a popular approach for 3D reconstruction, mostly due to its ability to converge reasonably fast, faithfully represent the scene and render (novel) views…
Rethinking Encoder-Decoder Flow Through Shared Structures
Frederik Laboyrie, Mehmet Kerim Yucel, Albert Saa-Garriga
Dense prediction tasks have enjoyed a growing complexity of encoder architectures, decoders, however, have remained largely the same. They rely on individual blocks decoding interm…
Trick-GS: A Balanced Bag of Tricks for Efficient Gaussian Splatting
Anil Armagan, Albert Saà-Garriga, Bruno Manganelli +2
Gaussian splatting (GS) for 3D reconstruction has become quite popular due to their fast training, inference speeds and high quality reconstruction. However, GS-based reconstructio…
CheapNVS: Real-Time On-Device Narrow-Baseline Novel View Synthesis
Konstantinos Georgiadis, Mehmet Kerim Yucel, Albert Saa-Garriga
Single-view novel view synthesis (NVS) is a notorious problem due to its ill-posed nature, and often requires large, computationally expensive approaches to produce tangible result…