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๐ฅ "Segmenting Anything". CRAZY! ๐ฅ
๐#Meta unveils a novel model and (1B+) dataset for neural segmentation ๐คฏ
๐Review https://bit.ly/3nM2uXx
๐Paper https://bit.ly/43788DC
๐Project https://segment-anything.com
๐Code github.com/facebookresearch/segment-anything
๐#Meta unveils a novel model and (1B+) dataset for neural segmentation ๐คฏ
๐Review https://bit.ly/3nM2uXx
๐Paper https://bit.ly/43788DC
๐Project https://segment-anything.com
๐Code github.com/facebookresearch/segment-anything
๐คฏ36โค16๐ฑ3๐2๐ฅ1๐ฅฐ1
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๐ชฌ META's Animated Drawings is out! ๐ชฌ
๐#META unveils an easy-to-use method for animating human-like figures drawn by children.
๐Review https://bit.ly/3mGeQQv
๐Paper arxiv.org/pdf/2303.12741.pdf
๐Project fairanimateddrawings.com
๐#META unveils an easy-to-use method for animating human-like figures drawn by children.
๐Review https://bit.ly/3mGeQQv
๐Paper arxiv.org/pdf/2303.12741.pdf
๐Project fairanimateddrawings.com
๐ฑ16๐ฅฐ5๐4๐2๐คฉ2โก1๐ฅ1๐พ1
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๐ฆ 6D Non-Prehensile Manipulation ๐ฆ
๐#META (+CMU) unveils HACMan, novel 6D non-prehensile manipulation of objects
๐Review https://bit.ly/3NP1jl1
๐Paper arxiv.org/pdf/2305.03942.pdf
๐Project hacman-2023.github.io
๐#META (+CMU) unveils HACMan, novel 6D non-prehensile manipulation of objects
๐Review https://bit.ly/3NP1jl1
๐Paper arxiv.org/pdf/2305.03942.pdf
๐Project hacman-2023.github.io
๐6๐ฅ4๐คฏ3๐ฑ1
๐ฆ Llama-2: the Open-Source "ChatGPT" ๐ฆ
๐GenAI, #Meta unveils Llama-2: a collection of LLMs ranging in scale 7-70B params. Challenging with #chatgpt, but open.
๐Review https://t.ly/bLJgP
๐Paper https://t.ly/AOXru
๐Project https://ai.meta.com/llama
๐GenAI, #Meta unveils Llama-2: a collection of LLMs ranging in scale 7-70B params. Challenging with #chatgpt, but open.
๐Review https://t.ly/bLJgP
๐Paper https://t.ly/AOXru
๐Project https://ai.meta.com/llama
๐คฏ19โค2๐ฅ1๐ฉ1
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๐ Controllable Synthetic Data (extending Image-Net) ๐
๐#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
๐Review https://t.ly/nCYs0
๐Paper arxiv.org/pdf/2308.03977.pdf
๐Project pug.metademolab.com
๐Code github.com/facebookresearch/PUG
๐#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
๐Review https://t.ly/nCYs0
๐Paper arxiv.org/pdf/2308.03977.pdf
๐Project pug.metademolab.com
๐Code github.com/facebookresearch/PUG
๐ฅ4โค2๐1๐คฉ1
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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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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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โ๏ธ Relighted 3D Hands ๐ค
๐#META unveils Re:InterHand: a large dataset of relighted 3D interacting hands
๐Review https://t.ly/I1dQk
๐Paper arxiv.org/pdf/2310.17768.pdf
๐Project mks0601.github.io/ReInterHand
๐Data github.com/mks0601/ReInterHand
๐#META unveils Re:InterHand: a large dataset of relighted 3D interacting hands
๐Review https://t.ly/I1dQk
๐Paper arxiv.org/pdf/2310.17768.pdf
๐Project mks0601.github.io/ReInterHand
๐Data github.com/mks0601/ReInterHand
๐คฏ8โค1๐ฑ1
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๐ Emu: image edit / video gen. ๐
๐#Meta the new SOTA in text-to-video generation and instruction-based image editing
๐ Review https://t.ly/PMTBc
๐ Paper (images): https://lnkd.in/eVadH-QS
๐ Project https://lnkd.in/eG8eWUJY
๐ Paper (video): https://lnkd.in/eVadH-QS
๐ Project https://lnkd.in/eu6Zu6gp
๐#Meta the new SOTA in text-to-video generation and instruction-based image editing
๐ Review https://t.ly/PMTBc
๐ Paper (images): https://lnkd.in/eVadH-QS
๐ Project https://lnkd.in/eG8eWUJY
๐ Paper (video): https://lnkd.in/eVadH-QS
๐ Project https://lnkd.in/eu6Zu6gp
๐ฅ8๐คฏ2๐1๐ฑ1
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๐ชRT Humanoid from Head-Mounted Sensors๐ช
๐#META (+CMU) announced SimXR, a method for controlling a simulated avatar from info obtained from AR/VR headsets
๐Review https://t.ly/Si2Mp
๐Paper arxiv.org/pdf/2403.06862.pdf
๐Project www.zhengyiluo.com/SimXR/
๐#META (+CMU) announced SimXR, a method for controlling a simulated avatar from info obtained from AR/VR headsets
๐Review https://t.ly/Si2Mp
๐Paper arxiv.org/pdf/2403.06862.pdf
๐Project www.zhengyiluo.com/SimXR/
โค12โก1๐1
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๐งคHOT3D Hand/Object Tracking๐งค
๐#Meta opens a novel egocentric dataset for 3D hand & object tracking. A new benchmark for vision-based understanding of 3D hand-object interactions. Dataset available ๐
๐Review https://t.ly/cD76F
๐Paper https://lnkd.in/e6_7UNny
๐Data https://lnkd.in/e6P-sQFK
๐#Meta opens a novel egocentric dataset for 3D hand & object tracking. A new benchmark for vision-based understanding of 3D hand-object interactions. Dataset available ๐
๐Review https://t.ly/cD76F
๐Paper https://lnkd.in/e6_7UNny
๐Data https://lnkd.in/e6P-sQFK
๐ฅ9โค3๐3๐2๐คฏ1
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๐ฅ๐ฅ SAM v2 is out! ๐ฅ๐ฅ
๐#Meta announced SAM 2, the novel unified model for real-time promptable segmentation in images and videos. 6x faster, it's the new SOTA by a large margin. Source Code, Dataset, Models & Demo released under permissive licenses๐
๐Review https://t.ly/oovJZ
๐Paper https://t.ly/sCxMY
๐Demo https://sam2.metademolab.com
๐Project ai.meta.com/blog/segment-anything-2/
๐Models github.com/facebookresearch/segment-anything-2
๐#Meta announced SAM 2, the novel unified model for real-time promptable segmentation in images and videos. 6x faster, it's the new SOTA by a large margin. Source Code, Dataset, Models & Demo released under permissive licenses๐
๐Review https://t.ly/oovJZ
๐Paper https://t.ly/sCxMY
๐Demo https://sam2.metademolab.com
๐Project ai.meta.com/blog/segment-anything-2/
๐Models github.com/facebookresearch/segment-anything-2
๐ฅ27โค10๐คฏ4๐2๐พ1
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๐ EFM3D: 3D Ego-Foundation ๐
๐#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released๐
๐Review https://t.ly/cDJv6
๐Paper arxiv.org/pdf/2406.10224
๐Project www.projectaria.com/datasets/aeo/
๐Repo github.com/facebookresearch/efm3d
๐#META presents EFM3D, the first benchmark for 3D object detection and surface regression on HQ annotated egocentric data of Project Aria. Datasets & Code released๐
๐Review https://t.ly/cDJv6
๐Paper arxiv.org/pdf/2406.10224
๐Project www.projectaria.com/datasets/aeo/
๐Repo github.com/facebookresearch/efm3d
๐ฅ9โค2๐2โก1๐1๐1
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๐ฅ CoTracker3 by #META is out! ๐ฅ
๐#Meta (+VGG Oxford) unveils CoTracker3, a new tracker that outperforms the previous SoTA by a large margin using only the 0.1% of the training data ๐คฏ๐คฏ๐คฏ
๐Review https://t.ly/TcRIv
๐Paper arxiv.org/pdf/2410.11831
๐Project cotracker3.github.io/
๐Code github.com/facebookresearch/co-tracker
๐#Meta (+VGG Oxford) unveils CoTracker3, a new tracker that outperforms the previous SoTA by a large margin using only the 0.1% of the training data ๐คฏ๐คฏ๐คฏ
๐Review https://t.ly/TcRIv
๐Paper arxiv.org/pdf/2410.11831
๐Project cotracker3.github.io/
๐Code github.com/facebookresearch/co-tracker
โค14๐ฅ3๐คฏ3๐พ2๐1๐ฑ1๐1
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โ๏ธ Universal Relightable Avatars โ๏ธ
๐#Meta unveils URAvatar, photorealistic & relightable avatars from phone scan with unknown illumination. Stunning results!
๐Review https://t.ly/U-ESX
๐Paper arxiv.org/pdf/2410.24223
๐Project junxuan-li.github.io/urgca-website
๐#Meta unveils URAvatar, photorealistic & relightable avatars from phone scan with unknown illumination. Stunning results!
๐Review https://t.ly/U-ESX
๐Paper arxiv.org/pdf/2410.24223
๐Project junxuan-li.github.io/urgca-website
โค11๐ฅ5โก1๐1
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โค๏ธโ๐ฅ Uncommon object in #3D โค๏ธโ๐ฅ
๐#META releases uCO3D, a new object-centric dataset for 3D AI. The largest publicly-available collection of HD videos of objects with 3D annotations that ensures full-360โฆ coverage. Code & data under CCA 4.0๐
๐Review https://t.ly/Z_tvA
๐Paper https://arxiv.org/pdf/2501.07574
๐Project https://uco3d.github.io/
๐Repo github.com/facebookresearch/uco3d
๐#META releases uCO3D, a new object-centric dataset for 3D AI. The largest publicly-available collection of HD videos of objects with 3D annotations that ensures full-360โฆ coverage. Code & data under CCA 4.0๐
๐Review https://t.ly/Z_tvA
๐Paper https://arxiv.org/pdf/2501.07574
๐Project https://uco3d.github.io/
๐Repo github.com/facebookresearch/uco3d
โค11โก2๐2๐1๐1๐คฉ1๐พ1
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โ๏ธ Relightable Full-Body Avatars โ๏ธ
๐#Meta unveils the first approach ever to jointly model the relightable appearance of the body, face, and hands of drivable avatars.
๐Review https://t.ly/kx9gf
๐Paper arxiv.org/pdf/2501.14726
๐Project neuralbodies.github.io/RFGCA
๐#Meta unveils the first approach ever to jointly model the relightable appearance of the body, face, and hands of drivable avatars.
๐Review https://t.ly/kx9gf
๐Paper arxiv.org/pdf/2501.14726
๐Project neuralbodies.github.io/RFGCA
โค3๐3๐ฅ3โก1๐คฏ1๐ข1๐คฉ1
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๐ฅ VideoJAM: #META's Video-Model (SOTA) ๐ฅ
๐#META's VideoJAM: the new SOTA (by large margin) in motion coherence for video generation, much better than SORA! A strong motion prior into any video-gen model. Impressive results, no code announced๐ฅฒ
๐Review https://shorturl.at/id7Bt
๐Paper https://arxiv.org/pdf/2502.02492
๐Project https://hila-chefer.github.io/videojam-paper.github.io/
๐#META's VideoJAM: the new SOTA (by large margin) in motion coherence for video generation, much better than SORA! A strong motion prior into any video-gen model. Impressive results, no code announced๐ฅฒ
๐Review https://shorturl.at/id7Bt
๐Paper https://arxiv.org/pdf/2502.02492
๐Project https://hila-chefer.github.io/videojam-paper.github.io/
๐ฅ9โค4๐1๐1๐คฉ1