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πΉοΈ CoDeF: Video Content Deformation Fields πΉοΈ
πCoDeF is a new type of video representation for video-editing tasks
πReview https://t.ly/PIVl-
πPaper arxiv.org/pdf/2308.07926.pdf
πProject https://qiuyu96.github.io/CoDeF
πCode https://github.com/qiuyu96/CoDeF
πCoDeF is a new type of video representation for video-editing tasks
πReview https://t.ly/PIVl-
πPaper arxiv.org/pdf/2308.07926.pdf
πProject https://qiuyu96.github.io/CoDeF
πCode https://github.com/qiuyu96/CoDeF
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Hello everybody,
a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood!
π₯ NO SPAM
π₯ NO COMMERCIAL
π₯ NO UNRESPECTFUL MESSAGEs
π§‘JUST AI & SCIENCE
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a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood!
π₯ NO SPAM
π₯ NO COMMERCIAL
π₯ NO UNRESPECTFUL MESSAGEs
π§‘JUST AI & SCIENCE
β οΈ BAN AT THE FIRST VIOLATION β οΈ
β€44π28π₯6π1π€―1πΎ1
AI with Papers - Artificial Intelligence & Deep Learning pinned Β«Hello everybody, a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope you will enjoy this new mood! π₯ NO SPAM π₯ NO COMMERCIAL π₯ NO UNRESPECTFUL MESSAGEs π§‘JUST AI & SCIENCE β οΈ BAN AT THE FIRSTβ¦Β»
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π¦ Instance-Level Semantics of Cells π¦
πTYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures
πReview https://t.ly/y-4VZ
πPaper arxiv.org/pdf/2308.12116.pdf
πProject christophreich1996.github.io/tyc_dataset/
πCode github.com/ChristophReich1996/TYC-Dataset
πData tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930
πTYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures
πReview https://t.ly/y-4VZ
πPaper arxiv.org/pdf/2308.12116.pdf
πProject christophreich1996.github.io/tyc_dataset/
πCode github.com/ChristophReich1996/TYC-Dataset
πData tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930
π8π₯3β€1β‘1π€―1
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π΅POCO: 3D HPS + Confidenceπ΅
π Novel framework for HPS: #3D human body + confidence in a single feed-forward pass
πReview https://t.ly/cDePe
πPaper arxiv.org/pdf/2308.12965.pdf
πProject https://poco.is.tue.mpg.de
π Novel framework for HPS: #3D human body + confidence in a single feed-forward pass
πReview https://t.ly/cDePe
πPaper arxiv.org/pdf/2308.12965.pdf
πProject https://poco.is.tue.mpg.de
π₯5π3β€2π€―1π±1
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π NeO360: NeRF for Sparse Outdoor π
π#Toyota (+GIT) unveils NeO360: 360β¦ outdoor scenes from a single or a few posed RGB images
πReview https://t.ly/JDJZg
πPaper arxiv.org/pdf/2308.12967.pdf
πProject zubair-irshad.github.io/projects/neo360.html
π#Toyota (+GIT) unveils NeO360: 360β¦ outdoor scenes from a single or a few posed RGB images
πReview https://t.ly/JDJZg
πPaper arxiv.org/pdf/2308.12967.pdf
πProject zubair-irshad.github.io/projects/neo360.html
β€13π3π₯2π₯°1π€―1
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π₯ Scenimefy: I-2-I for anime π₯
πS-Lab unveils a novel semi-supervised I-2-I translation framework + HD dataset for anime
πReview https://t.ly/IsdEG
πPaper arxiv.org/pdf/2308.12968.pdf
πCode https://github.com/Yuxinn-J/Scenimefy
πProject https://yuxinn-j.github.io/projects/Scenimefy.html
πS-Lab unveils a novel semi-supervised I-2-I translation framework + HD dataset for anime
πReview https://t.ly/IsdEG
πPaper arxiv.org/pdf/2308.12968.pdf
πCode https://github.com/Yuxinn-J/Scenimefy
πProject https://yuxinn-j.github.io/projects/Scenimefy.html
π₯°13β€2π₯1πΎ1
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π¨ Watch Your Steps: Editing by Text π¨
πThe novel SOTA in image & scene (text) editing via denoising diffusion models
πReview https://t.ly/fv9wn
πPaper arxiv.org/pdf/2308.08947.pdf
πProject ashmrz.github.io/WatchYourSteps
πThe novel SOTA in image & scene (text) editing via denoising diffusion models
πReview https://t.ly/fv9wn
πPaper arxiv.org/pdf/2308.08947.pdf
πProject ashmrz.github.io/WatchYourSteps
β€4π3π€―3π₯1
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π‘ Relighting NeRF π‘
πNeural implicit radiance representation for free viewpoint relighting of an object lit by a moving point light
πReview https://t.ly/J-3_L
πProject nrhints.github.io
πCode github.com/iamNCJ/NRHints
πPaper nrhints.github.io/pdfs/nrhints-sig23.pdf
πNeural implicit radiance representation for free viewpoint relighting of an object lit by a moving point light
πReview https://t.ly/J-3_L
πProject nrhints.github.io
πCode github.com/iamNCJ/NRHints
πPaper nrhints.github.io/pdfs/nrhints-sig23.pdf
π€―3π2β€1β‘1π₯1
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πͺΆ ReST: Multi-Camera MOT πͺΆ
πNovel reconfigurable two-steps graph model for multi-camera multi object video tracking (MC-MOT)
πReview https://t.ly/3C5tb
πPaper arxiv.org/pdf/2308.13229.pdf
πCode github.com/chengche6230/ReST
πNovel reconfigurable two-steps graph model for multi-camera multi object video tracking (MC-MOT)
πReview https://t.ly/3C5tb
πPaper arxiv.org/pdf/2308.13229.pdf
πCode github.com/chengche6230/ReST
π₯7β€3π€©2
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π²MagicEdit: Magic Video Editπ²
πMagicEdit: explicit disentangling content, structure & motion for Hi-Fi and temporally coherent video editing
πReport https://t.ly/tREX4
πPaper arxiv.org/pdf/2308.14749.pdf
πProject magic-edit.github.io
πCode github.com/magic-research/magic-edit
πMagicEdit: explicit disentangling content, structure & motion for Hi-Fi and temporally coherent video editing
πReport https://t.ly/tREX4
πPaper arxiv.org/pdf/2308.14749.pdf
πProject magic-edit.github.io
πCode github.com/magic-research/magic-edit
π₯°8β€4π3π₯1π±1π€©1
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βοΈ VideoCutLER: Simple UVIS βοΈ
πVideoCutLER is a simple unsupervised video instance segmentation (UVIS) method without relying on optical flows
πReview https://t.ly/PBBjG
πPaper arxiv.org/pdf/2308.14710.pdf
πProject people.eecs.berkeley.edu/~xdwang/projects/CutLER
πCode github.com/facebookresearch/CutLER/tree/main/videocutler
πVideoCutLER is a simple unsupervised video instance segmentation (UVIS) method without relying on optical flows
πReview https://t.ly/PBBjG
πPaper arxiv.org/pdf/2308.14710.pdf
πProject people.eecs.berkeley.edu/~xdwang/projects/CutLER
πCode github.com/facebookresearch/CutLER/tree/main/videocutler
π₯8π3β€2π€―1
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π¦ 3D Pigeons Pose & Tracking π¦
π 3D-MuPPET: estimate and track 3D poses of pigeons with multiple-views
πReview https://t.ly/jfAJJ
πPaper arxiv.org/pdf/2308.15316.pdf
πCode github.com/alexhang212/3D-MuPPET/
π 3D-MuPPET: estimate and track 3D poses of pigeons with multiple-views
πReview https://t.ly/jfAJJ
πPaper arxiv.org/pdf/2308.15316.pdf
πCode github.com/alexhang212/3D-MuPPET/
π€£17π€―14π4π₯°2β€1π€©1
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πRoboTAP: Dense Tracking for Few-Shot Imitationπ
πRoboTAP: novel dense tracking representation for robotic arm
πReview https://t.ly/MCO_V
πPaper arxiv.org/pdf/2308.15975.pdf
πProject https://robotap.github.io/
πCode github.com/deepmind/tapnet
πRoboTAP: novel dense tracking representation for robotic arm
πReview https://t.ly/MCO_V
πPaper arxiv.org/pdf/2308.15975.pdf
πProject https://robotap.github.io/
πCode github.com/deepmind/tapnet
π₯8π2π€―2π€©1
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βΊFACET: Fairness in Computer VisionβΊ
π#META AI opens a large, publicly available dataset for classification, detection & segmentation. Potential performance disparities & challenges across sensitive demographic attributes
πReview https://t.ly/mKn-t
πPaper arxiv.org/pdf/2309.00035.pdf
πDataset https://facet.metademolab.com/
π#META AI opens a large, publicly available dataset for classification, detection & segmentation. Potential performance disparities & challenges across sensitive demographic attributes
πReview https://t.ly/mKn-t
πPaper arxiv.org/pdf/2309.00035.pdf
πDataset https://facet.metademolab.com/
π₯10β€6π4π1
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βοΈ Doppelgangers in Structures βοΈ
πA novel learning-based approach for visual disambiguation: distinguishing illusory matches to produce correct, disambiguated #3D reconstructions
πReview https://t.ly/9yLot
πPaper arxiv.org/pdf/2309.02420.pdf
πCode github.com/RuojinCai/Doppelgangers
πProject doppelgangers-3d.github.io/
πA novel learning-based approach for visual disambiguation: distinguishing illusory matches to produce correct, disambiguated #3D reconstructions
πReview https://t.ly/9yLot
πPaper arxiv.org/pdf/2309.02420.pdf
πCode github.com/RuojinCai/Doppelgangers
πProject doppelgangers-3d.github.io/
π₯8π3π€―2π1
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π Tracking Anything with Decoupled VOS π
πA novel VOS approach that extends SAM for open-world video segmentation with no user input required
πReview https://t.ly/xeobR
πPaper arxiv.org/pdf/2309.03903.pdf
πProject hkchengrex.com/Tracking-Anything-with-DEVA
πCode github.com/hkchengrex/Tracking-Anything-with-DEVA
πColab https://colab.research.google.com/drive/1OsyNVoV_7ETD1zIE8UWxL3NXxu12m_YZ
πA novel VOS approach that extends SAM for open-world video segmentation with no user input required
πReview https://t.ly/xeobR
πPaper arxiv.org/pdf/2309.03903.pdf
πProject hkchengrex.com/Tracking-Anything-with-DEVA
πCode github.com/hkchengrex/Tracking-Anything-with-DEVA
πColab https://colab.research.google.com/drive/1OsyNVoV_7ETD1zIE8UWxL3NXxu12m_YZ
π₯13π6π€―4β€2π’1π€©1
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πͺ· Diffusive Consistent Video Editing πͺ·
π Weizmann Institute of Science unveils TokenFlow, a novel text-to-image diffusion model for text-driven video editing
πReview https://t.ly/ru8km
πPaper arxiv.org/pdf/2307.10373.pdf
πProject diffusion-tokenflow.github.io
πCode github.com/omerbt/TokenFlow
π Weizmann Institute of Science unveils TokenFlow, a novel text-to-image diffusion model for text-driven video editing
πReview https://t.ly/ru8km
πPaper arxiv.org/pdf/2307.10373.pdf
πProject diffusion-tokenflow.github.io
πCode github.com/omerbt/TokenFlow
β€9π6π₯2π€―1π±1π’1
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π₯π₯ #META's DINOv2 is now commercial! π₯π₯
πUniversal features for image classification, instance retrieval, video understanding, depth & semantic segmentation. Now suitable for commercial.
πReview https://t.ly/LNrGy
πPaper arxiv.org/pdf/2304.07193.pdf
πCode github.com/facebookresearch/dinov2
πDemo dinov2.metademolab.com/
πUniversal features for image classification, instance retrieval, video understanding, depth & semantic segmentation. Now suitable for commercial.
πReview https://t.ly/LNrGy
πPaper arxiv.org/pdf/2304.07193.pdf
πCode github.com/facebookresearch/dinov2
πDemo dinov2.metademolab.com/
π₯15π3β€1π€―1π±1
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π§FreeMan: towards #3D Humans π§
πFreeMan: the first large-scale, real-world, multi-view dataset for #3D human pose estimation. 11M frames!
πReview https://t.ly/ICxpA
πPaper arxiv.org/pdf/2309.05073.pdf
πProject wangjiongw.github.io/freeman
πFreeMan: the first large-scale, real-world, multi-view dataset for #3D human pose estimation. 11M frames!
πReview https://t.ly/ICxpA
πPaper arxiv.org/pdf/2309.05073.pdf
πProject wangjiongw.github.io/freeman
π6π€―4π₯°1