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๐ NeO360: NeRF for Sparse Outdoor ๐
๐#Toyota (+GIT) unveils NeO360: 360โฆ outdoor scenes from a single or a few posed RGB images
๐Review https://t.ly/JDJZg
๐Paper arxiv.org/pdf/2308.12967.pdf
๐Project zubair-irshad.github.io/projects/neo360.html
๐#Toyota (+GIT) unveils NeO360: 360โฆ outdoor scenes from a single or a few posed RGB images
๐Review https://t.ly/JDJZg
๐Paper arxiv.org/pdf/2308.12967.pdf
๐Project zubair-irshad.github.io/projects/neo360.html
โค13๐3๐ฅ2๐ฅฐ1๐คฏ1
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๐ฅ Scenimefy: I-2-I for anime ๐ฅ
๐S-Lab unveils a novel semi-supervised I-2-I translation framework + HD dataset for anime
๐Review https://t.ly/IsdEG
๐Paper arxiv.org/pdf/2308.12968.pdf
๐Code https://github.com/Yuxinn-J/Scenimefy
๐Project https://yuxinn-j.github.io/projects/Scenimefy.html
๐S-Lab unveils a novel semi-supervised I-2-I translation framework + HD dataset for anime
๐Review https://t.ly/IsdEG
๐Paper arxiv.org/pdf/2308.12968.pdf
๐Code https://github.com/Yuxinn-J/Scenimefy
๐Project https://yuxinn-j.github.io/projects/Scenimefy.html
๐ฅฐ13โค2๐ฅ1๐พ1
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๐จ Watch Your Steps: Editing by Text ๐จ
๐The novel SOTA in image & scene (text) editing via denoising diffusion models
๐Review https://t.ly/fv9wn
๐Paper arxiv.org/pdf/2308.08947.pdf
๐Project ashmrz.github.io/WatchYourSteps
๐The novel SOTA in image & scene (text) editing via denoising diffusion models
๐Review https://t.ly/fv9wn
๐Paper arxiv.org/pdf/2308.08947.pdf
๐Project ashmrz.github.io/WatchYourSteps
โค4๐3๐คฏ3๐ฅ1
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๐ก Relighting NeRF ๐ก
๐Neural implicit radiance representation for free viewpoint relighting of an object lit by a moving point light
๐Review https://t.ly/J-3_L
๐Project nrhints.github.io
๐Code github.com/iamNCJ/NRHints
๐Paper nrhints.github.io/pdfs/nrhints-sig23.pdf
๐Neural implicit radiance representation for free viewpoint relighting of an object lit by a moving point light
๐Review https://t.ly/J-3_L
๐Project nrhints.github.io
๐Code github.com/iamNCJ/NRHints
๐Paper nrhints.github.io/pdfs/nrhints-sig23.pdf
๐คฏ3๐2โค1โก1๐ฅ1
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๐ชถ ReST: Multi-Camera MOT ๐ชถ
๐Novel reconfigurable two-steps graph model for multi-camera multi object video tracking (MC-MOT)
๐Review https://t.ly/3C5tb
๐Paper arxiv.org/pdf/2308.13229.pdf
๐Code github.com/chengche6230/ReST
๐Novel reconfigurable two-steps graph model for multi-camera multi object video tracking (MC-MOT)
๐Review https://t.ly/3C5tb
๐Paper arxiv.org/pdf/2308.13229.pdf
๐Code github.com/chengche6230/ReST
๐ฅ7โค3๐คฉ2
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๐ฒMagicEdit: Magic Video Edit๐ฒ
๐MagicEdit: explicit disentangling content, structure & motion for Hi-Fi and temporally coherent video editing
๐Report https://t.ly/tREX4
๐Paper arxiv.org/pdf/2308.14749.pdf
๐Project magic-edit.github.io
๐Code github.com/magic-research/magic-edit
๐MagicEdit: explicit disentangling content, structure & motion for Hi-Fi and temporally coherent video editing
๐Report https://t.ly/tREX4
๐Paper arxiv.org/pdf/2308.14749.pdf
๐Project magic-edit.github.io
๐Code github.com/magic-research/magic-edit
๐ฅฐ8โค4๐3๐ฅ1๐ฑ1๐คฉ1
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โ๏ธ VideoCutLER: Simple UVIS โ๏ธ
๐VideoCutLER is a simple unsupervised video instance segmentation (UVIS) method without relying on optical flows
๐Review https://t.ly/PBBjG
๐Paper arxiv.org/pdf/2308.14710.pdf
๐Project people.eecs.berkeley.edu/~xdwang/projects/CutLER
๐Code github.com/facebookresearch/CutLER/tree/main/videocutler
๐VideoCutLER is a simple unsupervised video instance segmentation (UVIS) method without relying on optical flows
๐Review https://t.ly/PBBjG
๐Paper arxiv.org/pdf/2308.14710.pdf
๐Project people.eecs.berkeley.edu/~xdwang/projects/CutLER
๐Code github.com/facebookresearch/CutLER/tree/main/videocutler
๐ฅ8๐3โค2๐คฏ1
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๐ฆ 3D Pigeons Pose & Tracking ๐ฆ
๐ 3D-MuPPET: estimate and track 3D poses of pigeons with multiple-views
๐Review https://t.ly/jfAJJ
๐Paper arxiv.org/pdf/2308.15316.pdf
๐Code github.com/alexhang212/3D-MuPPET/
๐ 3D-MuPPET: estimate and track 3D poses of pigeons with multiple-views
๐Review https://t.ly/jfAJJ
๐Paper arxiv.org/pdf/2308.15316.pdf
๐Code github.com/alexhang212/3D-MuPPET/
๐คฃ17๐คฏ14๐4๐ฅฐ2โค1๐คฉ1
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๐RoboTAP: Dense Tracking for Few-Shot Imitation๐
๐RoboTAP: novel dense tracking representation for robotic arm
๐Review https://t.ly/MCO_V
๐Paper arxiv.org/pdf/2308.15975.pdf
๐Project https://robotap.github.io/
๐Code github.com/deepmind/tapnet
๐RoboTAP: novel dense tracking representation for robotic arm
๐Review https://t.ly/MCO_V
๐Paper arxiv.org/pdf/2308.15975.pdf
๐Project https://robotap.github.io/
๐Code github.com/deepmind/tapnet
๐ฅ8๐2๐คฏ2๐คฉ1
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โบFACET: Fairness in Computer Visionโบ
๐#META AI opens a large, publicly available dataset for classification, detection & segmentation. Potential performance disparities & challenges across sensitive demographic attributes
๐Review https://t.ly/mKn-t
๐Paper arxiv.org/pdf/2309.00035.pdf
๐Dataset https://facet.metademolab.com/
๐#META AI opens a large, publicly available dataset for classification, detection & segmentation. Potential performance disparities & challenges across sensitive demographic attributes
๐Review https://t.ly/mKn-t
๐Paper arxiv.org/pdf/2309.00035.pdf
๐Dataset https://facet.metademolab.com/
๐ฅ10โค6๐4๐1
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โ๏ธ Doppelgangers in Structures โ๏ธ
๐A novel learning-based approach for visual disambiguation: distinguishing illusory matches to produce correct, disambiguated #3D reconstructions
๐Review https://t.ly/9yLot
๐Paper arxiv.org/pdf/2309.02420.pdf
๐Code github.com/RuojinCai/Doppelgangers
๐Project doppelgangers-3d.github.io/
๐A novel learning-based approach for visual disambiguation: distinguishing illusory matches to produce correct, disambiguated #3D reconstructions
๐Review https://t.ly/9yLot
๐Paper arxiv.org/pdf/2309.02420.pdf
๐Code github.com/RuojinCai/Doppelgangers
๐Project doppelgangers-3d.github.io/
๐ฅ8๐3๐คฏ2๐1
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๐ Tracking Anything with Decoupled VOS ๐
๐A novel VOS approach that extends SAM for open-world video segmentation with no user input required
๐Review https://t.ly/xeobR
๐Paper arxiv.org/pdf/2309.03903.pdf
๐Project hkchengrex.com/Tracking-Anything-with-DEVA
๐Code github.com/hkchengrex/Tracking-Anything-with-DEVA
๐Colab https://colab.research.google.com/drive/1OsyNVoV_7ETD1zIE8UWxL3NXxu12m_YZ
๐A novel VOS approach that extends SAM for open-world video segmentation with no user input required
๐Review https://t.ly/xeobR
๐Paper arxiv.org/pdf/2309.03903.pdf
๐Project hkchengrex.com/Tracking-Anything-with-DEVA
๐Code github.com/hkchengrex/Tracking-Anything-with-DEVA
๐Colab https://colab.research.google.com/drive/1OsyNVoV_7ETD1zIE8UWxL3NXxu12m_YZ
๐ฅ13๐6๐คฏ4โค2๐ข1๐คฉ1
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๐ชท Diffusive Consistent Video Editing ๐ชท
๐ Weizmann Institute of Science unveils TokenFlow, a novel text-to-image diffusion model for text-driven video editing
๐Review https://t.ly/ru8km
๐Paper arxiv.org/pdf/2307.10373.pdf
๐Project diffusion-tokenflow.github.io
๐Code github.com/omerbt/TokenFlow
๐ Weizmann Institute of Science unveils TokenFlow, a novel text-to-image diffusion model for text-driven video editing
๐Review https://t.ly/ru8km
๐Paper arxiv.org/pdf/2307.10373.pdf
๐Project diffusion-tokenflow.github.io
๐Code github.com/omerbt/TokenFlow
โค9๐6๐ฅ2๐คฏ1๐ฑ1๐ข1
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๐ฅ๐ฅ #META's DINOv2 is now commercial! ๐ฅ๐ฅ
๐Universal features for image classification, instance retrieval, video understanding, depth & semantic segmentation. Now suitable for commercial.
๐Review https://t.ly/LNrGy
๐Paper arxiv.org/pdf/2304.07193.pdf
๐Code github.com/facebookresearch/dinov2
๐Demo dinov2.metademolab.com/
๐Universal features for image classification, instance retrieval, video understanding, depth & semantic segmentation. Now suitable for commercial.
๐Review https://t.ly/LNrGy
๐Paper arxiv.org/pdf/2304.07193.pdf
๐Code github.com/facebookresearch/dinov2
๐Demo dinov2.metademolab.com/
๐ฅ15๐3โค1๐คฏ1๐ฑ1
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๐งFreeMan: towards #3D Humans ๐ง
๐FreeMan: the first large-scale, real-world, multi-view dataset for #3D human pose estimation. 11M frames!
๐Review https://t.ly/ICxpA
๐Paper arxiv.org/pdf/2309.05073.pdf
๐Project wangjiongw.github.io/freeman
๐FreeMan: the first large-scale, real-world, multi-view dataset for #3D human pose estimation. 11M frames!
๐Review https://t.ly/ICxpA
๐Paper arxiv.org/pdf/2309.05073.pdf
๐Project wangjiongw.github.io/freeman
๐6๐คฏ4๐ฅฐ1
๐ฆ MagiCapture: HD Multi-Concept Portrait ๐ฆ
๐KAIST unveils MagiCapture: integrating subject and style concepts to generate high-resolution portrait images using just a few subject and style references
๐Review https://t.ly/c9rOo
๐Paper https://arxiv.org/pdf/2309.06895.pdf
๐KAIST unveils MagiCapture: integrating subject and style concepts to generate high-resolution portrait images using just a few subject and style references
๐Review https://t.ly/c9rOo
๐Paper https://arxiv.org/pdf/2309.06895.pdf
โค5๐ฅฐ1
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โฝ Dynamic NeRFs for Soccer โฝ
๐SoccerNeRF: first attempt of "cheap" NeRF applied to football for reconstructing soccer replays in space and time.
๐Review https://t.ly/Ywcvk
๐Paper arxiv.org/pdf/2309.06802.pdf
๐Project https://soccernerfs.isach.be/
๐Code github.com/iSach/SoccerNeRFs
๐SoccerNeRF: first attempt of "cheap" NeRF applied to football for reconstructing soccer replays in space and time.
๐Review https://t.ly/Ywcvk
๐Paper arxiv.org/pdf/2309.06802.pdf
๐Project https://soccernerfs.isach.be/
๐Code github.com/iSach/SoccerNeRFs
๐ฅ8โค4๐3๐คฉ2๐ฅฐ1
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โข๏ธ GlueStick: Graph Neural Matching โข๏ธ
๐GlueStick is joint deep matcher for points and lines that leverages the connectivity information between nodes to better glue them together
๐Review https://t.ly/Atxqo
๐Paper arxiv.org/pdf/2304.02008.pdf
๐Code https://github.com/cvg/GlueStick
๐GlueStick is joint deep matcher for points and lines that leverages the connectivity information between nodes to better glue them together
๐Review https://t.ly/Atxqo
๐Paper arxiv.org/pdf/2304.02008.pdf
๐Code https://github.com/cvg/GlueStick
๐ฅ11๐4โค1๐คฏ1๐คฉ1
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๐ซCPR-Coach: Neural Cardiopulmonary Resuscitation๐ซ
๐CPR-Coach: fine-grained action recognition in cardiopulmonary resuscitation
๐Review https://t.ly/Qbg4K
๐Paper arxiv.org/pdf/2309.11718.pdf
๐Code github.com/Shunli-Wang/CPR-Coach
๐Project shunli-wang.github.io/CPR-Coach
๐CPR-Coach: fine-grained action recognition in cardiopulmonary resuscitation
๐Review https://t.ly/Qbg4K
๐Paper arxiv.org/pdf/2309.11718.pdf
๐Code github.com/Shunli-Wang/CPR-Coach
๐Project shunli-wang.github.io/CPR-Coach
โค7๐ฅ3๐1
๐งช NeuralLabeling with NeRF ๐งช
๐Annotating a scene by generating segmentation masks, affordance maps, 2D bounding boxes, 3D BB, 6DOF poses, depth & meshes.
๐Review https://t.ly/1GPsj
๐Paper arxiv.org/pdf/2309.11966.pdf
๐Code github.com/FlorisE/neural-labeling
๐Project florise.github.io/neural_labeling_web
๐Annotating a scene by generating segmentation masks, affordance maps, 2D bounding boxes, 3D BB, 6DOF poses, depth & meshes.
๐Review https://t.ly/1GPsj
๐Paper arxiv.org/pdf/2309.11966.pdf
๐Code github.com/FlorisE/neural-labeling
๐Project florise.github.io/neural_labeling_web
๐5๐คฏ3๐ฅ2โค1๐ฅฐ1