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๐ฝ Neuralangelo Digital Twins. INSANE๐ฝ
๐ A novel framework from #Nvidia for Hi-Fi 3D Digital twins.
๐Review https://t.ly/rxoF4
๐Project research.nvidia.com/labs/dir/neuralangelo
๐Paper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
๐ A novel framework from #Nvidia for Hi-Fi 3D Digital twins.
๐Review https://t.ly/rxoF4
๐Project research.nvidia.com/labs/dir/neuralangelo
๐Paper research.nvidia.com/labs/dir/neuralangelo/paper.pdf
๐ฅ15๐4๐คฏ1
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๐ฆ ColorDiffuser: Text-to-Video Colorization ๐ฆ
๐HK University unveils ColorDiffuser: adapting pre-trained text-to-image latent diffusion model for video colorization
๐Review https://t.ly/XGv_
๐Paper arxiv.org/pdf/2306.01732.pdf
๐Project colordiffuser.github.io/
๐Code github.com/ColorDiffuser/ColorDiffuser
๐HK University unveils ColorDiffuser: adapting pre-trained text-to-image latent diffusion model for video colorization
๐Review https://t.ly/XGv_
๐Paper arxiv.org/pdf/2306.01732.pdf
๐Project colordiffuser.github.io/
๐Code github.com/ColorDiffuser/ColorDiffuser
๐คฏ8โค2๐คฉ1
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๐ป Extending Mona Lisa with AI ๐ป
๐ A guy on Reddit extends Mona Lisa Painting with #Photoshop AI. The result is surprising.
๐More https://t.ly/j_2r
๐ A guy on Reddit extends Mona Lisa Painting with #Photoshop AI. The result is surprising.
๐More https://t.ly/j_2r
๐คฏ20๐5๐คฉ4๐ฅ3๐ฑ2๐คฃ2โก1
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๐ธ Segment Anything in HQ ๐ธ
๐HQ-SAM: SAM with the ability to accurately segment objects, maintaining promptable design, efficiency, zero-shot generalizability
๐Review https://t.ly/GxX5B
๐Paper arxiv.org/pdf/2306.01567.pdf
๐Models github.com/SysCV/SAM-HQ
๐HQ-SAM: SAM with the ability to accurately segment objects, maintaining promptable design, efficiency, zero-shot generalizability
๐Review https://t.ly/GxX5B
๐Paper arxiv.org/pdf/2306.01567.pdf
๐Models github.com/SysCV/SAM-HQ
๐ฅ18๐4๐คฏ1๐ฑ1๐1
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๐ Track Everything Everywhere ๐
๐#Google unveils OmniMotion: full-length motion tracking for every pixel in every frame of video.
๐Review https://t.ly/Krvw
๐Paper arxiv.org/pdf/2306.05422.pdf
๐Project omnimotion.github.io/
๐Demo omnimotion.github.io/#interactive_demo
๐Code github.com/qianqianwang68/omnimotion
๐#Google unveils OmniMotion: full-length motion tracking for every pixel in every frame of video.
๐Review https://t.ly/Krvw
๐Paper arxiv.org/pdf/2306.05422.pdf
๐Project omnimotion.github.io/
๐Demo omnimotion.github.io/#interactive_demo
๐Code github.com/qianqianwang68/omnimotion
๐ฅ23โค5๐คฏ3๐คฉ1๐ฉ1
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๐๏ธ Scene Five: Through Her Eyes ๐๏ธ
๐ #3D scene reconstruction of what a person is observing using only the reflections of their eyes
๐Review https://t.ly/uBO6
๐Paper arxiv.org/pdf/2306.09348.pdf
๐Project https://world-from-eyes.github.io/
๐ #3D scene reconstruction of what a person is observing using only the reflections of their eyes
๐Review https://t.ly/uBO6
๐Paper arxiv.org/pdf/2306.09348.pdf
๐Project https://world-from-eyes.github.io/
๐คฏ28๐ฅ12๐ฉ2๐คฉ1
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๐งฟ NeRF-Supervised Deep Stereo ๐งฟ
๐A novel pioneering pipeline for training deep stereo networks WITH NO ground-truth
๐Review https://t.ly/c7j-
๐Project nerfstereo.github.io/
๐Dataset https://amsacta.unibo.it/id/eprint/7218/
๐Code github.com/fabiotosi92/NeRF-Supervised-Deep-Stereo
๐Paper https://openaccess.thecvf.com/content/CVPR2023/papers/Tosi_NeRF-Supervised_Deep_Stereo_CVPR_2023_paper.pdf
๐A novel pioneering pipeline for training deep stereo networks WITH NO ground-truth
๐Review https://t.ly/c7j-
๐Project nerfstereo.github.io/
๐Dataset https://amsacta.unibo.it/id/eprint/7218/
๐Code github.com/fabiotosi92/NeRF-Supervised-Deep-Stereo
๐Paper https://openaccess.thecvf.com/content/CVPR2023/papers/Tosi_NeRF-Supervised_Deep_Stereo_CVPR_2023_paper.pdf
๐ฅฐ8๐คฉ3โค1๐1๐ฉ1๐1
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๐ซฃ Text-Guided Adversarial Makeup ๐ซฃ
๐Novel facial privacy protection via adversarial latent codes. Makeup vs Face Recognition.
๐Review https://t.ly/pBCP
๐Paper arxiv.org/pdf/2306.10008.pdf
๐Code github.com/fahadshamshad/Clip2Protect
๐Novel facial privacy protection via adversarial latent codes. Makeup vs Face Recognition.
๐Review https://t.ly/pBCP
๐Paper arxiv.org/pdf/2306.10008.pdf
๐Code github.com/fahadshamshad/Clip2Protect
โค6๐1๐ฅ1๐ฅฐ1๐ฉ1
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๐ฆท Few-Shot Geometry-Aware Keypoints ๐ฆท
๐UBC (+Flawless AI) unveils the new SOTA in semantic keypoints localization. Suitable for faces, animals, cars, mouth, teeth & more
๐Review https://t.ly/-0qN
๐Paper arxiv.org/pdf/2303.17216.pdf
๐Project xingzhehe.github.io/FewShot3DKP/
๐UBC (+Flawless AI) unveils the new SOTA in semantic keypoints localization. Suitable for faces, animals, cars, mouth, teeth & more
๐Review https://t.ly/-0qN
๐Paper arxiv.org/pdf/2303.17216.pdf
๐Project xingzhehe.github.io/FewShot3DKP/
๐คฏ10๐4โค2โก2๐2๐คฉ2๐ฅ1
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๐ Fooling Neural Forensic Classifiers ๐
๐Adversarial faces able to fool the forensic classifiers, while remaining undetectable by humans
๐Review https://t.ly/33Cc
๐Paper arxiv.org/pdf/2306.13091.pdf
๐Project koushiksrivats.github.io/face_attribute_attack
๐Code github.com/koushiksrivats/face_attribute_attack
๐Adversarial faces able to fool the forensic classifiers, while remaining undetectable by humans
๐Review https://t.ly/33Cc
๐Paper arxiv.org/pdf/2306.13091.pdf
๐Project koushiksrivats.github.io/face_attribute_attack
๐Code github.com/koushiksrivats/face_attribute_attack
๐ข6โค4๐2๐ฑ2๐พ2๐1๐คฏ1๐1
panohead_overview-min.gif
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๐ฅ PanoHead: 3D Full-Head Synthesis ๐ฅ
๐#ByteDance (+UW-M) unveils PanoHead: 360โฆ view-consistent portraits from a single-view image
๐Review https://t.ly/MrLNR
๐Paper arxiv.org/pdf/2303.13071.pdf
๐Project sizhean.github.io/panohead
๐Code github.com/sizhean/panohead
๐#ByteDance (+UW-M) unveils PanoHead: 360โฆ view-consistent portraits from a single-view image
๐Review https://t.ly/MrLNR
๐Paper arxiv.org/pdf/2303.13071.pdf
๐Project sizhean.github.io/panohead
๐Code github.com/sizhean/panohead
๐ฅ7โค4๐คฏ3๐ฑ1
AI with Papers - Artificial Intelligence & Deep Learning
๐ Drag-GAN: user-friendly image-manipulation ๐ ๐ Manual deforming of (real and generated) images over pose, shape, expression and layout. ๐Review https://bit.ly/3BFyXlR ๐Paper arxiv.org/pdf/2305.10973.pdf ๐Project vcai.mpi-inf.mpg.de/projects/DragGANโฆ
Linkedin
๐ฅ๐ฅ Source Code of Drag-GAN IS OUT! | Alessandro Ferrari | 40 comments
๐ฅ๐ฅ Source Code of Drag-GAN IS OUT! ๐ฅ๐ฅ
๐Manual deforming of (real and generated) images over pose, shape, expression and layout. Source Code just released a few hours ago ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Max Planck + MIT + #Google AR/VR = ๐คฏ
โ Supervising handle points to moveโฆ
๐Manual deforming of (real and generated) images over pose, shape, expression and layout. Source Code just released a few hours ago ๐
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:
โ Max Planck + MIT + #Google AR/VR = ๐คฏ
โ Supervising handle points to moveโฆ
๐ฅ25๐ฑ6โค3๐ฅฐ1๐คฏ1
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๐ฎSAM-PT: Segment Anything+Tracking๐ฎ
๐SAM-PT is the first method to utilize sparse point propagation for Video Object Segmentation (VOS).
๐Review https://t.ly/QLMG
๐Paper arxiv.org/pdf/2307.01197.pdf
๐Project www.vis.xyz/pub/sam-pt/
๐Code github.com/SysCV/sam-pt
๐SAM-PT is the first method to utilize sparse point propagation for Video Object Segmentation (VOS).
๐Review https://t.ly/QLMG
๐Paper arxiv.org/pdf/2307.01197.pdf
๐Project www.vis.xyz/pub/sam-pt/
๐Code github.com/SysCV/sam-pt
๐ฅ14โค7๐คฏ3๐1๐ฑ1
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๐ชฉ DISCO: Human Dance Generation ๐ชฉ
๐NTU (+ #Microsoft) unveils DISCO: a big step towards the Human Dance Generation.
๐Review https://t.ly/cNGX
๐Paper arxiv.org/pdf/2307.00040.pdf
๐Project disco-dance.github.io/
๐Code github.com/Wangt-CN/DisCo
๐NTU (+ #Microsoft) unveils DISCO: a big step towards the Human Dance Generation.
๐Review https://t.ly/cNGX
๐Paper arxiv.org/pdf/2307.00040.pdf
๐Project disco-dance.github.io/
๐Code github.com/Wangt-CN/DisCo
๐ฅ13๐ฅฐ4๐2โก1๐1๐พ1
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๐ฃ๏ธ STAR.: 3D-tracking w/ attention paradigm ๐ฃ๏ธ
๐#Mercedes STAR: e2e 3D object tracking that follows the tracking-by-attention paradigm
๐Review https://t.ly/JoGj
๐Paper arxiv.org/pdf/2306.17602.pdf
๐Project simondoll.github.io/publications/star_track
๐#Mercedes STAR: e2e 3D object tracking that follows the tracking-by-attention paradigm
๐Review https://t.ly/JoGj
๐Paper arxiv.org/pdf/2306.17602.pdf
๐Project simondoll.github.io/publications/star_track
๐14๐ฅ1๐ฅฐ1๐1
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๐ก Text2Cinemagraphs: Cinemagraph from text ๐ก
๐CMU (+ #Snap) unveils a fully automated method for creating cinemagraphs from text descriptions
๐Review https://t.ly/BwZs6
๐Paper arxiv.org/pdf/2307.03190.pdf
๐Project text2cinemagraph.github.io/website
๐Code github.com/text2cinemagraph/text2cinemagraph
๐CMU (+ #Snap) unveils a fully automated method for creating cinemagraphs from text descriptions
๐Review https://t.ly/BwZs6
๐Paper arxiv.org/pdf/2307.03190.pdf
๐Project text2cinemagraph.github.io/website
๐Code github.com/text2cinemagraph/text2cinemagraph
โค12๐คฏ3๐ฑ1๐คฉ1
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๐ฅTest-Time Training on fire ๐ฅ
๐Extending the TTT to the streaming setting. Suitable for Panoptic, Instance & Colorization.
๐Review https://t.ly/eZYA
๐Paper arxiv.org/pdf/2307.05014.pdf
๐Project https://video-ttt.github.io/
๐Code github.com/renwang435/video-ttt-release
๐Extending the TTT to the streaming setting. Suitable for Panoptic, Instance & Colorization.
๐Review https://t.ly/eZYA
๐Paper arxiv.org/pdf/2307.05014.pdf
๐Project https://video-ttt.github.io/
๐Code github.com/renwang435/video-ttt-release
๐ฅ10๐3โก1๐คฏ1
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๐ Deepfake via casual self-scan ๐
๐TAU presents a novel approach to reenact an ID using only a casual self-scan
๐Review https://t.ly/9T8Wi
๐Paper arxiv.org/pdf/2307.06307.pdf
๐Project arielazary.github.io/PGR
๐TAU presents a novel approach to reenact an ID using only a casual self-scan
๐Review https://t.ly/9T8Wi
๐Paper arxiv.org/pdf/2307.06307.pdf
๐Project arielazary.github.io/PGR
๐คฏ7๐6โค5๐ฅ1๐ฑ1
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๐ช Extreme Human Pose Estimation ๐ช
๐RePoGen: novel synthetic data generator of extreme/realistic poses of humans
๐Review https://t.ly/ecBvM
๐Paper arxiv.org/pdf/2307.06737.pdf
๐Project mirapurkrabek.github.io/RePoGen-paper
๐Code github.com/MiraPurkrabek/RePoGen
๐RePoGen: novel synthetic data generator of extreme/realistic poses of humans
๐Review https://t.ly/ecBvM
๐Paper arxiv.org/pdf/2307.06737.pdf
๐Project mirapurkrabek.github.io/RePoGen-paper
๐Code github.com/MiraPurkrabek/RePoGen
๐ฅ12๐2๐1๐คฏ1๐ฑ1
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๐ก DATID-3D: Text-to-3D Generation ๐ก
๐ A novel domain adaptation method for 3D via text-to-image diffusion. ๐ค-Demo available!
๐Review https://t.ly/TCL-B
๐Paper arxiv.org/pdf/2211.16374.pdf
๐Project gwang-kim.github.io/datid_3d/
๐Code github.com/gwang-kim/DATID-3D
๐ค huggingface.co/spaces/gwang-kim/DATID-3D
๐Colab colab.research.google.com/drive/1e9NSVB7x_hjz-nr4K0jO4rfTXILnNGtA?usp=sharing
๐ A novel domain adaptation method for 3D via text-to-image diffusion. ๐ค-Demo available!
๐Review https://t.ly/TCL-B
๐Paper arxiv.org/pdf/2211.16374.pdf
๐Project gwang-kim.github.io/datid_3d/
๐Code github.com/gwang-kim/DATID-3D
๐ค huggingface.co/spaces/gwang-kim/DATID-3D
๐Colab colab.research.google.com/drive/1e9NSVB7x_hjz-nr4K0jO4rfTXILnNGtA?usp=sharing
๐คฏ5