TiNeuVox

Capture video of the person performing actions.

Preprocess the video frames to extract coordinate data.

Train the TiNeuVox model using the video data.

Render novel views of the person in motion.

Evaluate rendering quality using PSNR, SSIM, and LPIPS.

Capture video of the deforming object.

Extract coordinate data and temporal information.

Train the TiNeuVox model.

Generate animations with novel perspectives and lighting conditions.

Assess animation quality using established metrics.

Capture a 360-degree video of the environment.

Process the video frames to extract 3D data.

Train the TiNeuVox model to reconstruct the environment.

Integrate the model into a VR application.

Allow users to navigate and interact within the virtual environment.

Capture dynamic scenes of urban environments.

Train the TiNeuVox model to reconstruct these scenes.

Simulate vehicle movement within the reconstructed environment.

Use the simulated data to train autonomous driving algorithms.

Evaluate the performance of the algorithms in realistic conditions.

Capture a sparse set of images of the dynamic scene.

Train the TiNeuVox model using these images.

Generate new views from arbitrary camera positions.

Refine the generated views for improved visual quality.

Deploy novel view generation for applications like virtual tourism.