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Found 6 papers, 5 papers with code
DerainNeRF: 3D Scene Estimation with Adhesive Waterdrop Removal
When capturing images through the glass during rainy or snowy weather conditions, the resulting images often contain waterdrops adhered on the glass surface, and these waterdrops significantly degrade the image quality and performance of many computer vision algorithms.
BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting
In this paper, we introduce a novel approach, named BAD-Gaussians (Bundle Adjusted Deblur Gaussian Splatting), which leverages explicit Gaussian representation and handles severe motion-blurred images with inaccurate camera poses to achieve high-quality scene reconstruction.
Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting
Building upon our MVControl architecture, we employ a unique hybrid diffusion guidance method to direct the optimization process.
MVControl: Adding Conditional Control to Multi-view Diffusion for Controllable Text-to-3D Generation
Our approach enables the generation of controllable multi-view images and view-consistent 3D content.
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
USB-NeRF is able to correct rolling shutter distortions and recover accurate camera motion trajectory simultaneously under the framework of NeRF, by modeling the physical image formation process of a RS camera.
BAD-NeRF: Bundle Adjusted Deblur Neural Radiance Fields
Our approach models the physical image formation process of a motion blurred image, and jointly learns the parameters of NeRF and recovers the camera motion trajectories during exposure time.
