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Fast Dynamic Radiance Fields with Time-Aware Neural Voxels
A fast neural rendering framework for dynamic scenes, representing scenes with time-aware neural voxels to accelerate the training speed and maintain high rendering quality. -
TMT Dataset
The TMT dataset consists of static and dynamic parts. The static part is synthesized using the place dataset [58] for static scenes. The dynamic part is generated using the... -
Beats dataset
A real-world dataset for dynamic articulated objects, used to test the proposed Knowledge NeRF method. -
Telescope dataset
A real-world dataset for dynamic articulated objects, used to test the proposed Knowledge NeRF method. -
Postbox dataset
A dataset for dynamic articulated objects, used to test the proposed Knowledge NeRF method. -
Shiny Blender dataset
A dataset for dynamic articulated objects, used to test the proposed Knowledge NeRF method. -
NVIDIA Dynamic Scene Dataset
The dataset used in the paper is the NVIDIA Dynamic Scene Dataset, which contains 8 diverse scenes with 12 sequences captured by synchronized cameras at fixed positions. -
DAVIS Dataset
The DAVIS dataset contains 60 training sequences and 30 validation sequences, with high-quality densely-annotated segmentation mask annotation for each frame. -
Stereo Blur Dataset
A dataset of dynamic scenes with motion blur, curated for the task of dynamic neural radiance field synthesis.