1
Hierarchical Text-Conditional Image Generation with CLIP Latents
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Disentangling Architecture and Training for Optical Flow
3
High-Resolution Image Synthesis with Latent Diffusion Models
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STALP: Style Transfer with Auxiliary Limited Pairing
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AutoFlow: Learning a Better Training Set for Optical Flow
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Learning to Estimate Hidden Motions with Global Motion Aggregation
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Learning Long Term Style Preserving Blind Video Temporal Consistency
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Arbitrary Video Style Transfer via Multi-Channel Correlation
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Interactive video stylization using few-shot patch-based training
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Learning by Analogy: Reliable Supervision From Transformations for Unsupervised Optical Flow Estimation
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RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
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Improving Optical Flow on a Pyramid Level
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
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Stylizing video by example
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A Flexible Convolutional Solver for Fast Style Transfers
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Learning Linear Transformations for Fast Image and Video Style Transfer
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A Lightweight Optical Flow CNN —Revisiting Data Fidelity and Regularization
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Learning Blind Video Temporal Consistency
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Fixing Weight Decay Regularization in Adam
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Occlusion-aware Video Temporal Consistency
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PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
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Artistic Style Transfer for Videos and Spherical Images
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Neural style transfer: a paradigm shift for image-based artistic rendering?
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Deep bilateral learning for real-time image enhancement
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Real-Time Neural Style Transfer for Videos
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Universal Style Transfer via Feature Transforms
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Neural Style Transfer: A Review
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Characterizing and Improving Stability in Neural Style Transfer
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MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
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The 2017 DAVIS Challenge on Video Object Segmentation
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Coherent Online Video Style Transfer
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FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
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Optical Flow Estimation Using a Spatial Pyramid Network
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Pruning Filters for Efficient ConvNets
35
Densely Connected Convolutional Networks
36
Image Style Transfer Using Convolutional Neural Networks
37
A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation
38
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
39
Fast Optical Flow Using Dense Inverse Search
40
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
41
Blind video temporal consistency
42
Region-based temporally consistent video post-processing
43
FlowNet: Learning Optical Flow with Convolutional Networks
44
Adam: A Method for Stochastic Optimization
45
Color Me Noisy: Example‐based Rendering of Hand‐colored Animations with Temporal Noise Control
46
A Naturalistic Open Source Movie for Optical Flow Evaluation
47
Practical temporal consistency for image-based graphics applications
48
Temporal noise control for sketchy animation
49
Coherent noise for non-photorealistic rendering
50
A Dynamic Noise Primitive for Coherent Stylization
51
GradientShop: A gradient-domain optimization framework for image and video filtering
52
PatchMatch: a randomized correspondence algorithm for structural image editing
53
Fourier Analysis of the 2D Screened Poisson Equation for Gradient Domain Problems
54
Video watercolorization using bidirectional texture advection
55
Real-time video abstraction
57
Processing images and video for an impressionist effect
58
Paint by numbers: abstract image representations
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Image style transfer © 2023 The Authors. Computer Graphics Forum published by Eurographics and
60
Volumetric Correspondence Networks for Optical Flow
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Consistent Filtering of Videos and Dense Light-Fields Without Optic-Flow
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Neural Information Processing Systems (Red Hook, NY, USA
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Torch-pruning: A pytorch pruning toolkit for structured neural network pruning and automatic layer dependency maintaining., 2019
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Supplementary Material for LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation
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pytorch-pwc: a reimplementation of pwc-net in pytorch that matches the official caffe version
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of 14 S. Shekhar et al. / Interactive Control over spatial pyramid network
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Interactive Control over Temporal Consistency while Stylizing Video Streams spatial pyramid network
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Unpaired image-to-image translation using cycle-consistent adversarial networks
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Temporally Coherent Video Stylization
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State of the ‘Art’: A Taxonomy of Artistic Stylization Techniques for Images and Video (cid:63)
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On the momentum term in gradient descent learning algorithms
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SIGGRAPH '90, Association for Computing Machinery
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Pixar Animation Studios,