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Found 4 papers, 3 papers with code
Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting
Through extensive analysis of SfM initialization in the frequency domain and analysis of a 1D regression task with multiple 1D Gaussians, we propose a novel optimization strategy dubbed RAIN-GS (Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting), that successfully trains 3D Gaussians from random point clouds.
Context Enhanced Transformer for Single Image Object Detection
With the increasing importance of video data in real-world applications, there is a rising need for efficient object detection methods that utilize temporal information.
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation
Employing monocular depth estimation (MDE) networks, pretrained on large-scale RGB-D datasets, with powerful generalization capability would be a key to solving this problem: however, using MDE in conjunction with NeRF comes with a new set of challenges due to various ambiguity problems exhibited by monocular depths.
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimation
We propose MaskingDepth, a novel semi-supervised learning framework for monocular depth estimation to mitigate the reliance on large ground-truth depth quantities.
