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Released at
#CVPR2019, MediaPipe is Google's new framework for media processing pipelines, combining model-based inference via TensorFlow with traditional CV tasks like optical flow, pose tracking, and more. Used in existing projects like Motion Stills. https://sites.google.com/view/perception-cv4arvr/mediapipe …pic.twitter.com/js2S3qu750 -
Ending my
#CVPR2019 conference as a Crazy Rich Bayesian! Go Bayesians! pic.twitter.com/NEq9qpkaTX
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Now available for commercial use on NGC, pix2pixHD developed by
@NVIDIA researchers generates high-resolution photorealistic images from high-level labels.#CVPR2019 https://ngc.nvidia.com/catalog/models/nvidia:pix2pixhd … -
When video description meets bounding boxes! We are now releasing data/code/models/leaderboard (yes, everything) on our
#CVPR2019 oral paper Grounded Video Description: Paper: https://lnkd.in/g-fs79K Dataset (158k bboxes on 52k captions):https://lnkd.in/g-pSKzfPrikaži ovu nit -
If you have any doubts about the applicability of CNNs to local feature detection for robust pose estimation, come to our Deep Charuco poster today at
#CVPR2019 . This videos shows a shadow effect and traditional methods are simply too frail. Red=fail http://charuco.net pic.twitter.com/31vfkGu9GX -
Best paper award at
#CVPR2019 main idea: seeing around the corner at non-line-of-sight (NLOS) objects by using Fermat paths, which is a new theory of how NLOS photons follow specific geometric paths. http://imaging.cs.cmu.edu/fermat_paths/assets/cvpr2019.pdf …pic.twitter.com/IMj1E4fnYs
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I liked the DeepMapping paper from Ding and Feng at
#CVPR2019. A bit similar to DIP, they use deep learning machinery to solve a surprising optimisation problem (no learning on a dataset): pose graph alignment for a set of pose scans. https://arxiv.org/abs/1811.11397@czarnowskijpic.twitter.com/mOBLwslMwx -
Learn about Learning from Unlabeled Videos at
#CVPR2019, Sunday in Room E, 9:00am Fresh posters and keynotes: Antonio Torralba, Noah Snavely, Andrew Zisserman, Bill Freeman, Abhinav Gupta, Kristen Grauman https://sites.google.com/view/luv2019/home?authuser=0 …Prikaži ovu nit -
If you're at
#CVPR2019 kindly visit me present our work on "Cycle Consistency for robust VQA" in Grand Ballroom at 14.10. My@facebookai co-authors will be there to answer all your questions in the poster session #184 that follows. Dataset + Code + Paper:https://facebookresearch.github.io/VQA-Rephrasings/ … -
If you enjoy
AND realtime visual-inertial SLAM, @Occipital is hosting a happy hour tomorrow at 5pm. DM me for details!#CVPR2019 pic.twitter.com/vmLD5HZ9eNPrikaži ovu nit -
This year Google is a proud Platinum Sponsor of
#cvpr2019, held in Long Beach, CA. If you’re attending, drop by the Google booth for some demos and chat with our researchers about their work on the field’s most interesting challenges! Learn more below! https://goo.gle/2KnBBUS -
We're launching a http://valeo.ai blog for sharing our latest work and reflections on research for safer and increasingly autonomous vehicles. The first post describes our recent
#CVPR2019 paper ADVENT for unsupervised domain adaptation: https://medium.com/@valeo.ai/advent-adversarial-entropy-minimization-for-domain-adaptation-in-semantic-segmentation-dba21934430b … -
NVIDIA Research will present 20 papers at
#CVPR2019, including 11 orals. Full list is here: https://nvda.ws/31xiZab . Check it out!pic.twitter.com/p39jHx4cp0
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Y. Niitani of Preferred Networks gave an oral presentation at
#CVPR2019 "Sampling Techniques for Large-Scale Object Detection from Sparsely Annotated Objects" used to win 2nd prize @ Google AI Open Images challenge (w/ Akiba, Kerola, Ogawa, Sano & Suzuki) http://openaccess.thecvf.com/content_CVPR_2019/papers/Niitani_Sampling_Techniques_for_Large-Scale_Object_Detection_From_Sparsely_Annotated_Objects_CVPR_2019_paper.pdf … pic.twitter.com/jbQjC7BO4u
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Deep Flow-Guided Video Inpainting
#CVPR2019 By@ccloy Completing a missing flow is easier than filling in pixels of a missing region directly. SoTA on DAVIS and YouTube-VOS Code https://github.com/nbei/Deep-Flow-Guided-Video-Inpainting … ArXiv https://arxiv.org/abs/1905.02884 pic.twitter.com/Qyj28rXThu -
At
#CVPR2019? Visit the Google booth at 10:15 to learn about MediaPipe (http://g.co/mediapipe ), an open source framework for building machine learning pipelines, along with the many methods submitted to the recent Challenge on Learned Image Compression (http://www.compression.cc/ )pic.twitter.com/9uteIcgfrc
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The Computer Vision team is seeking PhD students and recent graduates with a background in research and engineering. Create and build state-of-the-art AI in the areas of computer vision, NLP, and ML as a Software Engineer: https://aka.ms/AA5emyd
#CVPR2019 -
For those interested in some of the latest self-driving research (especially those participating in our
@Kaggle competition), we’ve collected our favorite self-driving content from#CVPR2019 in our latest reader's digest. Read them here: https://medium.com/lyftlevel5/cvpr-digest-9195adbd5d0c … -
"A General and Adaptive Robust Loss Function" by Jonathan T. Barron
#CVPR2019 http://youtu.be/BmNKbnF69eY pic.twitter.com/VOaSsqBQLt
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【CVPR 2019 速報】を更新しました。230ページの内容になりました! https://www.slideshare.net/cvpaperchallenge/cvpr-2019 … CVPR 2019 論文サマリはこちらをご覧ください http://xpaperchallenge.org/cv/survey/cvpr2019_summaries/listall/ …
#cvpr2019
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