Search Results for author:
Found 8 papers, 6 papers with code
OSS Mentor A framework for improving developers contributions via deep reinforcement learning
In open source project governance, there has been a lot of concern about how to measure developers' contributions.
PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution
3D neural networks are widely used in real-world applications (e. g., AR/VR headsets, self-driving cars).
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
To overcome this challenge, we propose a generic new approach that bridges the gap between image-conditional and recent modulated unconditional generative architectures via co-modulation of both conditional and stochastic style representations.
Ranked #3 on
Image Inpainting
on FFHQ 512 x 512
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Self-driving cars need to understand 3D scenes efficiently and accurately in order to drive safely.
Ranked #1 on
Robust 3D Semantic Segmentation
on SemanticKITTI-C
Differentiable Augmentation for Data-Efficient GAN Training
Furthermore, with only 20% training data, we can match the top performance on CIFAR-10 and CIFAR-100.
Ranked #1 on
Image Generation
on CIFAR-10 (20% data)
MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
In this paper, we propose an asymmetric occlusion-aware feature matching module, which can learn a rough occlusion mask that filters useless (occluded) areas immediately after feature warping without any explicit supervision.
Ranked #2 on
Optical Flow Estimation
on KITTI 2012
Recursive Cascaded Networks for Unsupervised Medical Image Registration
We present recursive cascaded networks, a general architecture that enables learning deep cascades, for deformable image registration.
Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network
3D medical image registration is of great clinical importance.
