cv논문
| Deeper Depth Prediction with Fully Convolutional Residual Networks (IEEE 2016) |
| Unsupervised Learning of Depth and Ego-Motion from Video (CVPR 2017) |
| Unsupervised Monocular Depth Estimation with Left-Right Consistency (CVPR 2017) |
| PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image (CVPR 2018) |
| Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints (CVPR 2018) |
| Learning the Depths of Moving People by Watching Frozen People (CVPR 2019) |
| Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics (CVPR Workshop on Visual Odometry & Computer Vision Applications Based on Location Clues (VOCVALC) (2019)) |
| Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras (ICCV 2019) |
| Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos (AAAI 2019) |
| Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics (AAAI 19) |
| Consistent Video Depth Estimation (Siggraph 2020) |
| Incorporating long-range consistency in cnn-based texture generation (ICLR 2017) |
| Deep photo style transfer (CVPR 2017) |
| Photorealistic style transfer with screened poisson equation (BMVC 2017) |
| A closedform solution to photorealistic image stylization (ECCV 2018) |
| Visual attribute transfer through deep image analogy (ACM ToG 2017) |
| The contextual loss for image transformation with non-aligned data (ECCV 2018) |
| PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup (CVPR 2018) |
| Improved texture networks: Maximizing quality and diversity in feed-forward stylization and texture synthesis (CVPR 2017) |
| Stylebank: An explicit representation for neural image style transfer (CVPR 2017) |
| Avatarnet: Multi-scale zero-shot style transfer by feature decoration (CVPR 2018) |
| Arbitrary Style Transfer with Style-Attentional Networks (CVPR 2019) |
| Arbitrary style transfer in real-time with adaptive instance normalization (ICCV 2017) |
| Universal style transfer via feature transforms (NIPS 2017) |
| Understanding generalized whitening and coloring transform for universal style transfer (ICCV 2019) |
| Multimodel style transfer via graph cuts (ICCV 2019) |
| 2016.WACV.Is image super-resolution helpful for other vision tasks? Super Resolution (Enhancement) |
| 2017.CVPR.Learning from Simulated and Unsupervised Image through Adversarial Trainin Simulation (SimGAN) (synthesized data(3D 눈 그림) -> 현실성 높여보자.(refine)) |
| 2017.CVPR.StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation Multi-Domain Transfer (StarGAN) |
| 2015.ICCV.Unsupervised Visual Representation Learning by Context Prediction |
| 2016.CVPR.Context Encoders: Feature Learning by Inpainting |
| 2016.ECCV.Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles |
| 이미지 9조각 나누고, 위치 맞추게 하는 Unsupervised learning |
| 2018.CVPR.Deep Video Generation, Prediction and Completion of Human Action Sequences |
| human action prediction 비디오 영상 액션 프레임 주고, 다음 프레임 영상 생성 |
| 2019.CVPR.A Style-Based Generator Architecture for Generative Adversarial Networks |
| 2014.CVPR.Rich feature hierarchies for accurate object detection and semantic segmentation (R-CNN) |
| 2015.PAMI.Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition (SPPNet) |
| 2015.ICCV.Fast R-CNN |
| 2015.NIPS.Faster r-cnn: Towards real-time object detection with region proposal networks (Faster R-CNN) |
| 2015.ICCV.AttentionNet: Aggregating Weak Directions for Accurate Object Detection |
| 2016.CVPR.You Only Look Once:Unified, Real-Time Object Detection (YOLO) (v4까지 읽어보기) |
| 2016.ECCV.SSD:Single shot multibox detector (SSD) |
| FlowNet: Learning optical flow with convolutional networks (ICCV 2015) |
| FlowNet 2.0: Evolution of optical flow estimation with deep networks (CVPR 2017) |
| CNN-based patch matching for optical flow with thresholded hinge embedding loss (CVPR 2017) |
| Optical flow estimation using a spatial pyramid network (CVPR 2017) |
| A lightweight convolutional neural network for optical flow estimation (CVPR 2018) |
| PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume (CVPR 2018) |
| Occlusion aware unsupervised learning of optical flow (CVPR 2018) |
| Iterative residual refinement for joint optical flow and occlusion estimation (CVPR 2019) |
| SelFlow: Self-supervised learning of optical flow (CVPR 2019) |
| Unsupervised learning of multi-frame optical flow with occlusions (ECCV 2018) |
| Conditional prior networks for optical flow (ECCV 2018) |
| Semi-supervised learning for optical flow with generative adversarial networks (NIPS 2017) |
| Unsupervised deep learning for optical flow estimation (AAAI 2017) |
| UnFlow: Unsupervised learning of optical flow with a bidirectional census loss (AAAI 2018) |
| Learning optical flow with unlabeled data distillation (AAAI 2019) |
| Visual Saliency Detection Based on Multiscale Deep CNN Features (TIP 2016) |
| Shallow and Deep Convolutional Networks for Saliency Prediction (CVPR 2016) |
| GraB: Visual Saliency via Novel Graph Model and Background Priors (CVPR 2016) |
| DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection (CVPR 2016) |
| Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective (CVPR 2018) |
| Pyramid Feature Attention Network for Saliency Detection (CVPR 2019) |
| Multi-Source Weak Supervision for Saliency Detection (CVPR 2019) |
| Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection (ECCV 2018) |
| Learning Uncertain Convolutional Features for Accurate Saliency Detection (ICCV 2017) |
| Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation (ICCV 2019) |
| Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection (ICCV 2019) |
| A Unified Multiple Graph Learning and Convolutional Network Model for Co-saliency Estimation (ACM Multimedia 2019) |
| 2015.ICML.Show, Attend, and Tell: Neural Image Caption generation with visual attention |
| 2015.CVPR.Long-term recurrent convolutional networks for visual recognition and description |
| 2016.CVPR.Fei-Fei.Densecap: Fully convolutional localization networks for dense captioning |
| 2017.ICCV.Grad-cam: Visual explanations from deep networks via gradient-based localization |
| 2018.CVPR.Bottom-up and top-down attention for image captioning and visual question answering |
Github 사용법