-
CIFAR-100, MNIST, ImageNet, MIT67, SUN397, Places205
The dataset used in this paper for object recognition on CIFAR-100, MNIST, and ImageNet, and scene recognition on MIT67, SUN397, and Places205. -
Learning Multiple Layers of Features from Tiny Images
The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image. -
Neural 3D Video Synthesis from Multi-View Video
The DyNeRF dataset contains 3D dynamic scenes with moving or deforming objects. -
Streaming Radiance Fields for 3D Video Synthesis
The MeetRoom dataset contains 3D dynamic scenes with moving or deforming objects. -
D-NeRF: Neural Radiance Fields for Dynamic Scenes
The D-NeRF dataset contains 3D dynamic scenes with moving or deforming objects. -
CIFAR-10 and ImageNet
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the CIFAR-10 and ImageNet datasets. -
ModelNet40
Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...
