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NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
In this paper, we introduce NBNet, a novel framework for image denoising...
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Practical Deep Raw Image Denoising on Mobile Devices
Deep learning-based image denoising approaches have been extensively stu...
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Arbitrary Video Style Transfer via Multi-Channel Correlation
Video style transfer is getting more attention in AI community for its n...
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FPConv: Learning Local Flattening for Point Convolution
We introduce FPConv, a novel surface-style convolution operator designed...
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LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning
We describe a policy learning approach to map visual inputs to driving c...
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PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation
In this work, we present a novel data-driven method for robust 6DoF obje...
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Disentangled Image Matting
Most previous image matting methods require a roughly-specificed trimap ...
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Semi-supervised Skin Detection by Network with Mutual Guidance
In this paper we present a new data-driven method for robust skin detect...
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Frame-Recurrent Video Inpainting by Robust Optical Flow Inference
In this paper, we present a new inpainting framework for recovering miss...
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Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
In this paper, we present new data pre-processing and augmentation techn...
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When AWGN-based Denoiser Meets Real Noises
Discriminative learning based image denoisers have achieved promising pe...
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GIF2Video: Color Dequantization and Temporal Interpolation of GIF images
Graphics Interchange Format (GIF) is a highly portable graphics format t...
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GeoNet: Deep Geodesic Networks for Point Cloud Analysis
Surface-based geodesic topology provides strong cues for object semantic...
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Deep Part Induction from Articulated Object Pairs
Object functionality is often expressed through part articulation -- as ...
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Video Inpainting by Jointly Learning Temporal Structure and Spatial Details
We present a new data-driven video inpainting method for recovering miss...
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Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
We introduce a large-scale 3D shape understanding benchmark using data a...
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High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference
We propose a data-driven method for recovering miss-ing parts of 3D shap...
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Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks
We present a new local descriptor for 3D shapes, directly applicable to ...
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