Search Results for author:
Found 7 papers, 4 papers with code
Personalized Federated Learning with First Order Model Optimization
While federated learning traditionally aims to train a single global model across decentralized local datasets, one model may not always be ideal for all participating clients.
World-Consistent Video-to-Video Synthesis
This is because they lack knowledge of the 3D world being rendered and generate each frame only based on the past few frames.
Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter
Specifically, we directly treat the whole encoded feature map of the input texture as transposed convolution filters and the features' self-similarity map, which captures the auto-correlation information, as input to the transposed convolution.
Hierarchical Multi-Scale Attention for Semantic Segmentation
Multi-scale inference is commonly used to improve the results of semantic segmentation.
Ranked #6 on
Semantic Segmentation
on Cityscapes val
(using extra training data)
Panoptic-based Image Synthesis
Conditional image synthesis for generating photorealistic images serves various applications for content editing to content generation.
Improving Semantic Segmentation via Video Propagation and Label Relaxation
In this paper, we present a video prediction-based methodology to scale up training sets by synthesizing new training samples in order to improve the accuracy of semantic segmentation networks.
Ranked #2 on
Semantic Segmentation
on KITTI Semantic Segmentation
(using extra training data)
Partial Convolution based Padding
In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks.
