computer-vision-research-papers

A list of Computer Vision research papers that I found interesting.

I will continue adding more papers, whenever I come across something interesting.

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• Paper on the "classical" approaches to image-based image synthesis is Photo Clip Art: http://graphics.cs.cmu.edu/projects/photoclipart/

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• ImageNet: A Large-Scale Hierarchical Image Database:

  Website: http://www.image-net.org/

  Paper: http://www.image-net.org/papers/imagenet_cvpr09.pdf

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• ImageNet Classification with Deep Convolutional Neural Networks. Alex Krizhevsky, Ilya Sutskever, Geoffrey E Hinton. NIPS 2012.

  http://www.cs.toronto.edu/~fritz/absps/imagenet.pdf

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• Interesting paper on learning how to design deep neural network architectures.

  https://arxiv.org/pdf/1611.02167v2.pdf

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• Sketch2Photo: Internet Image Montage.

  Project Page: http://cg.cs.tsinghua.edu.cn/montage/main.htm

  Paper: http://cg.cs.tsinghua.edu.cn/papers/SiggraphAsia_2009_sketch2photo.pdf

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• How Do Humans Sketch Objects?

  Project page: http://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/

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• BIING: Binarized Normed Gradients for Objectness Estimation

  Project page: http://mmcheng.net/bing/

  Paper: http://mmcheng.net/mftp/Papers/ObjectnessBING.pdf

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• What makes Paris look like Paris?

  Project page: http://graphics.cs.cmu.edu/projects/whatMakesParis/

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• DeepFace: Closing the Gap to Human-Level Performance in Face Verification.

  Paper: https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf

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• Robust Video Segment Proposals with Painless Occlusion Handling.

  Project Page: https://web.engr.oregonstate.edu/~lif/SegTrack2/Occlusion/

  Paper: https://web.engr.oregonstate.edu/~lif/SegTrack2/Occlusion/occlusion_paper.pdf

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• DynamicFusion: Reconstruction and Tracking of Non-rigid Scenes in Real-Time

  Project Page: http://grail.cs.washington.edu/projects/dynamicfusion/

  Paper: http://grail.cs.washington.edu/projects/dynamicfusion/papers/DynamicFusion.pdf

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• Deep neural networks are easily fooled: High confidence predictions for unrecognizable images.

  Project page: http://www.evolvingai.org/fooling

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• A Neural Algorithm of Artistic Style

  Paper: https://arxiv.org/abs/1508.06576

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• Understanding deep features with computer-generated imagery

  Paper: https://arxiv.org/abs/1506.01151

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• Learning Visual Biases from Human Imagination

  Paper: http://web.mit.edu/vondrick/imagination/paper.pdf

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• FaceNet: A Unified Embedding for Face Recognition and Clustering

  Paper: https://arxiv.org/abs/1503.03832

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• Joint Embeddings of Shapes and Images via CNN Image Purification

  Paper: https://shapenet.cs.stanford.edu/projects/JointEmbedding/

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• The Sketchy Database: Learning to Retrieve Badly Drawn Bunnies

  Project Page: http://sketchy.eye.gatech.edu/

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• Do Deep Convolutional Nets Really Need to be Deep and Convolutional?

  https://arxiv.org/abs/1603.05691

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• Unsupervised Learning of Visual Representations using Videos

  Paper: http://www.cs.cmu.edu/~xiaolonw/papers/unsupervised_video.pdf

  Project Page: http://www.cs.cmu.edu/~xiaolonw/unsupervise.html

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• XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

  Paper: https://arxiv.org/abs/1603.05279

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• Deep Residual Learning for Image Recognition.

  Paper: http://arxiv.org/abs/1512.03385

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• Learning Aligned Cross-Modal Representations from Weakly Aligned Data

  Project Page: https://projects.csail.mit.edu/cmplaces/

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• Visually Indicated Sounds

  vis.csail.mit.edu

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• "What happens if..." Learning to Predict the Effect of Forces in Images

  http://allenai.org/plato/forces/

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• YOLO9000: Better, Faster, Stronger

  https://arxiv.org/abs/1612.08242

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• Visual Dialog

  Paper: https://arxiv.org/abs/1611.08669

  Project Page: http://visualdialog.org/

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• Generative Adversarial Nets

  Paper: https://arxiv.org/pdf/1406.2661.pdf

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• Unsupervised Representation Learning with Deep Convolutional GANs

  Paper: https://arxiv.org/abs/1511.06434

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• Object Contour Detection with a Fully Convolutional Encoder-Decoder Network.

  Project Page: https://eng.ucmerced.edu/people/jyang44/objectContourDetection.html

  Paper: https://arxiv.org/pdf/1603.04530.pdf

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• Photo Realistic Style Transfer - Recent work in transferring style between images.

  Paper: https://arxiv.org/abs/1703.07511

  Code: https://github.com/luanfujun/deep-photo-styletransfer

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• Context Encoders: Feature Learning by Inpainting

  https://people.eecs.berkeley.edu/~pathak/papers/cvpr16.pdf

  https://arxiv.org/abs/1604.07379

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• Generative Adversarial Text-to-Image Synthesis

  Project page - https://github.com/reedscot/icml2016

  Paper - http://arxiv.org/abs/1605.05396

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• Generative Visual Manipulation on the Natural Image Manifold

  Project page - http://people.eecs.berkeley.edu/~junyanz/projects/gvm/

  Paper - https://arxiv.org/pdf/1609.03552v2.pdf

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• Improved Techniques for Training GANs

  Paper - https://arxiv.org/abs/1606.03498

  Code - https://github.com/openai/improved-gan

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• Conditional Image Generation with PixelCNN Decoders

  Paper - https://papers.nips.cc/paper/6527-conditional-image-generation-with-pixelcnn-decoders.pdf

  Code - https://github.com/anantzoid/Conditional-PixelCNN-decoder

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• Attribute2Image: Conditional Image Generation from Visual Attributes

  Paper: https://drive.google.com/file/d/0B9Q4vh7pPrOOdXpVTGZ6a1FlZW8/view

  Project Page: https://sites.google.com/site/attribute2image/

  Presentation Slides: https://docs.google.com/presentation/d/1qOaWY3qMviGRJm2QFMyYN3zgVcXQIEmmVNW56DiT_4I/edit#slide=id.g1d6af2990f_0_95

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• Semantic Segmentation using Adversarial Networks

  Paper - https://arxiv.org/abs/1611.08408

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• NetVLAD: CNN architecture for weakly supervised place recognition.

  paper: https://arxiv.org/abs/1511.07247

  project page: http://www.di.ens.fr/willow/research/netvlad/

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• Image-to-Image Translation with Conditional Adversarial Nets.

  Project - https://phillipi.github.io/pix2pix/

  Have fun with the demo! - https://affinelayer.com/pixsrv/

  Follow up work: CycleGAN - https://github.com/junyanz/CycleGAN

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• StackGAN: Text to Photo-realistic Image Synthesis with Stacked GANs

  Paper : https://arxiv.org/pdf/1612.03242v1.pdf

  Github : https://github.com/hanzhanggit/StackGAN

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• Neural Architecture Search with Reinforcement Learning

  Paper: https://arxiv.org/abs/1611.01578

  OpenReview Discussion: https://openreview.net/forum?id=r1Ue8Hcxg

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