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Found 6 papers, 4 papers with code
Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
The proposed architecture, termed as NICE-GAN, exhibits two advantageous patterns over previous approaches: First, it is more compact since no independent encoding component is required; Second, this plug-in encoder is directly trained by the adversary loss, making it more informative and trained more effectively if a multi-scale discriminator is applied.
Transformer for Graphs: An Overview from Architecture Perspective
In this survey, we provide a comprehensive review of various Graph Transformer models from the architectural design perspective.
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
After the great success of Vision Transformer variants (ViTs) in computer vision, it has also demonstrated great potential in domain adaptive semantic segmentation.
Ranked #7 on
Semantic Segmentation
on SYNTHIA-to-Cityscapes
Subequivariant Graph Reinforcement Learning in 3D Environments
Learning a shared policy that guides the locomotion of different agents is of core interest in Reinforcement Learning (RL), which leads to the study of morphology-agnostic RL.
Equivariant Local Reference Frames for Unsupervised Non-rigid Point Cloud Shape Correspondence
Based on the assumption of local rigidity, one solution for reducing complexity is to decompose the overall shape into independent local regions using Local Reference Frames (LRFs) that are invariant to SE(3) transformations.
Knowledge Representation Learning with Contrastive Completion Coding
Knowledge representation learning (KRL) has been used in plenty of knowledge-driven tasks.
