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Found 4 papers, 2 papers with code
Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling
Our Long Short-Term Memory Video Rescaling Network (LSTM-VRN) leverages temporal information in the low-resolution video to form an explicit prediction of the missing high-frequency information for upscaling.
Weakly-Supervised Image Semantic Segmentation Using Graph Convolutional Networks
One common approach to this task is to propagate the activation scores of Class Activation Maps (CAMs) using a random-walk mechanism in order to arrive at complete pseudo labels for training a semantic segmentation network in a fully-supervised manner.
NeuralODF: Learning Omnidirectional Distance Fields for 3D Shape Representation
We propose Omnidirectional Distance Fields (ODFs), a new 3D shape representation that encodes geometry by storing the depth to the object's surface from any 3D position in any viewing direction.
DiVa-360: The Dynamic Visual Dataset for Immersive Neural Fields
Advances in neural fields are enabling high-fidelity capture of the shape and appearance of dynamic 3D scenes.
