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Found 7 papers, 1 papers with code
SRGS: Super-Resolution 3D Gaussian Splatting
This approach relies on the representation power of Gaussian primitives to provide a high-quality rendering.
VQ-NeRV: A Vector Quantized Neural Representation for Videos
This block incorporates a codebook mechanism to discretize the network's shallow residual features and inter-frame residual information effectively.
Gaussian Splashing: Dynamic Fluid Synthesis with Gaussian Splatting
We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS.
ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields
This framework aims to guide the NeRF model to synthesize high-resolution novel views via single-scene internal learning rather than requiring any external high-resolution training data.
FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image
Precise Tooth Cone Beam Computed Tomography (CBCT) image segmentation is crucial for orthodontic treatment planning.
Learning Photometric Feature Transform for Free-form Object Scan
We propose a novel framework to automatically learn to aggregate and transform photometric measurements from multiple unstructured views into spatially distinctive and view-invariant low-level features, which are fed to a multi-view stereo method to enhance 3D reconstruction.
Human Behavior Recognition Method Based on CEEMD-ES Radar Selection
First, this method decomposes and reconstructs the radar signal according to the difference in the reflected echo frequency between the limbs and the trunk of the human body.
