π« AlphaGeometry: Olympiad-level AI π«
π Theorem prover for Euclidean plane geometry that sidesteps the need for human demonstrations by
synthesizing millions of theorems and proofs across different levels of complexity π€―
πReview https://t.ly/2-Z7C
πPaper https://lnkd.in/g3QkqwCE
πBlog https://lnkd.in/ge-mpM7q
πRepo https://lnkd.in/gHjwks_9
π Theorem prover for Euclidean plane geometry that sidesteps the need for human demonstrations by
synthesizing millions of theorems and proofs across different levels of complexity π€―
πReview https://t.ly/2-Z7C
πPaper https://lnkd.in/g3QkqwCE
πBlog https://lnkd.in/ge-mpM7q
πRepo https://lnkd.in/gHjwks_9
π€―20π3π₯°2π€©1
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π¦ XINC: Pixels to Neurons π¦
πeXplaining the Implicit Neural Canvas (XINC) from the University of Maryland, is a unified framework for explaining properties of INRs by examining the strength of each neuronβs contribution to each output pixel
πReview https://t.ly/wwAmz
πPaper arxiv.org/pdf/2401.10217.pdf
πProject namithap10.github.io/xinc
πRepo github.com/namithap10/xinc
πeXplaining the Implicit Neural Canvas (XINC) from the University of Maryland, is a unified framework for explaining properties of INRs by examining the strength of each neuronβs contribution to each output pixel
πReview https://t.ly/wwAmz
πPaper arxiv.org/pdf/2401.10217.pdf
πProject namithap10.github.io/xinc
πRepo github.com/namithap10/xinc
π€―9π3π2π₯1
π½ One Model <-> All Segmentations π½
π 10+ different segmentation tasks in one framework, including image-level, video-level, interactive segmentation, & open-vocabulary segmentation. All in one!
πReview https://t.ly/fywVz
πPaper https://lnkd.in/dw3S4B74
πProject https://lnkd.in/dzHT9v45
πRepo https://lnkd.in/d6fDCnSp
π 10+ different segmentation tasks in one framework, including image-level, video-level, interactive segmentation, & open-vocabulary segmentation. All in one!
πReview https://t.ly/fywVz
πPaper https://lnkd.in/dw3S4B74
πProject https://lnkd.in/dzHT9v45
πRepo https://lnkd.in/d6fDCnSp
π₯17π5β€2π₯°1πΎ1
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π» GARField: Group Anything π»
π GARField is a novel approach for decomposing #3D scenes into a hierarchy of semantically meaningful groups from posed image inputs.
πReview https://t.ly/6Hkeq
πPaper https://lnkd.in/d28mfRcZ
πProject https://lnkd.in/dzYdRNKy
πRepo (coming) https://lnkd.in/d2VeRJCS
π GARField is a novel approach for decomposing #3D scenes into a hierarchy of semantically meaningful groups from posed image inputs.
πReview https://t.ly/6Hkeq
πPaper https://lnkd.in/d28mfRcZ
πProject https://lnkd.in/dzYdRNKy
πRepo (coming) https://lnkd.in/d2VeRJCS
π8β€3π₯°1π€©1
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π₯ Depth Anything: new SOTA π₯
πDepth Anything: the new SOTA in monocular depth estimation (MDE), trained with 1.5M labeled images and 62M+ unlabeled images jointly. It's the new SOTA!
πReview https://t.ly/tCBwO
πPaper https://lnkd.in/djx-9k2J
πProject https://lnkd.in/dYetqZFa
πRepo https://lnkd.in/d87CrUGv
πDemoπ€ https://lnkd.in/dJhvKBep
πDepth Anything: the new SOTA in monocular depth estimation (MDE), trained with 1.5M labeled images and 62M+ unlabeled images jointly. It's the new SOTA!
πReview https://t.ly/tCBwO
πPaper https://lnkd.in/djx-9k2J
πProject https://lnkd.in/dYetqZFa
πRepo https://lnkd.in/d87CrUGv
πDemoπ€ https://lnkd.in/dJhvKBep
π₯17β€3π₯°2π€©2
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π ULTRA-Realistic Avatar π
πNovel 3D avatar with enhanced fidelity of geometry, and superior quality of physically based rendering (PBR) textures without unwanted lighting.
πReview https://t.ly/B3BEu
πProject https://lnkd.in/dkUQHFEV
πPaper https://lnkd.in/dtEQxrBu
πCode coming π©·
πNovel 3D avatar with enhanced fidelity of geometry, and superior quality of physically based rendering (PBR) textures without unwanted lighting.
πReview https://t.ly/B3BEu
πProject https://lnkd.in/dkUQHFEV
πPaper https://lnkd.in/dtEQxrBu
πCode coming π©·
π©17β€5π2π€©1
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π₯Lumiere: SOTA video-genπ₯
π#Google unveils Lumiere: Space-Time Diffusion Model for Realistic Video Generation. It's the new SOTA, tasks: Text-to-Video, Video Stylization, Cinemagraphs & Video Inpainting.
πReview https://t.ly/nalJR
πPaper https://lnkd.in/d-PvrGjT
πProject https://t.ly/gK8hz
π#Google unveils Lumiere: Space-Time Diffusion Model for Realistic Video Generation. It's the new SOTA, tasks: Text-to-Video, Video Stylization, Cinemagraphs & Video Inpainting.
πReview https://t.ly/nalJR
πPaper https://lnkd.in/d-PvrGjT
πProject https://t.ly/gK8hz
π₯18β€4π3π2π€©2π₯°1π€―1π©1
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π§ͺ SUPIR: SOTA restoration π§ͺ
πSUPIR is the new SOTA in image restoration; suitable for restoration of blurry objects, defining the material texture of objects, and adjusting restoration based on high-level semantics
πReview https://t.ly/wgObH
πProject https://supir.xpixel.group/
πPaper https://lnkd.in/dZPYcUuq
πDemo coming π©· but no code announced :(
πSUPIR is the new SOTA in image restoration; suitable for restoration of blurry objects, defining the material texture of objects, and adjusting restoration based on high-level semantics
πReview https://t.ly/wgObH
πProject https://supir.xpixel.group/
πPaper https://lnkd.in/dZPYcUuq
πDemo coming π©· but no code announced :(
β€8π₯4π₯°1πΎ1
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π«§ SAM + Open Models π«§
πGrounded SAM (w/ DINO) as an open-set detector to combine with SAM. It can seamlessly integrate with other Open-World models to accomplish more intricate visual tasks.
πReview https://t.ly/FwasQ
πPaper arxiv.org/pdf/2401.14159.pdf
πCode github.com/IDEA-Research/Grounded-Segment-Anything
πGrounded SAM (w/ DINO) as an open-set detector to combine with SAM. It can seamlessly integrate with other Open-World models to accomplish more intricate visual tasks.
πReview https://t.ly/FwasQ
πPaper arxiv.org/pdf/2401.14159.pdf
πCode github.com/IDEA-Research/Grounded-Segment-Anything
π₯9π2π1πΎ1
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π’"Virtual Try-All" by #Amazon π’
π#Amazon announces βDiffuse to Chooseβ: diffusion-based image-conditioned inpainting for VTON. Virtually place any e-commerce item in any setting.
πReview https://t.ly/at07Y
πPaper https://lnkd.in/dxR7nGtd
πProject diffuse2choose.github.io/
π#Amazon announces βDiffuse to Chooseβ: diffusion-based image-conditioned inpainting for VTON. Virtually place any e-commerce item in any setting.
πReview https://t.ly/at07Y
πPaper https://lnkd.in/dxR7nGtd
πProject diffuse2choose.github.io/
β€15π7π€―4π₯1π₯°1
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𦩠WildRGB-D: Objects in the Wild π¦©
π#NVIDIA unveils a novel RGB-D object dataset captured in the wild: ~8500 recorded objects, ~20,000 RGBD videos, 46 categories with corresponding masks and 3D point clouds.
πReview https://t.ly/WCqVz
πData github.com/wildrgbd/wildrgbd
πPaper arxiv.org/pdf/2401.12592.pdf
πProject wildrgbd.github.io/
π#NVIDIA unveils a novel RGB-D object dataset captured in the wild: ~8500 recorded objects, ~20,000 RGBD videos, 46 categories with corresponding masks and 3D point clouds.
πReview https://t.ly/WCqVz
πData github.com/wildrgbd/wildrgbd
πPaper arxiv.org/pdf/2401.12592.pdf
πProject wildrgbd.github.io/
π9β€3π₯2π1π€©1π1
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πEasyVolcap: Accelerating Neural Volumetricπ
πNovel #PyTorch library for accelerating neural video:volumetric video capturing, reconstruction & rendering
πReview https://t.ly/8BISl
πPaper arxiv.org/pdf/2312.06575.pdf
πCode github.com/zju3dv/EasyVolcap
πNovel #PyTorch library for accelerating neural video:volumetric video capturing, reconstruction & rendering
πReview https://t.ly/8BISl
πPaper arxiv.org/pdf/2312.06575.pdf
πCode github.com/zju3dv/EasyVolcap
π₯10π2β€1π₯°1π1π€©1
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π Rock-Track announced! π
πRock-Track: the evolution of Poly-MOT, the previous SOTA in 3D MOT Tracking-By-Detection framework.
πReview https://t.ly/hC0ak
πRepo, coming: https://lnkd.in/dtDkPwCC
πPaper coming
πRock-Track: the evolution of Poly-MOT, the previous SOTA in 3D MOT Tracking-By-Detection framework.
πReview https://t.ly/hC0ak
πRepo, coming: https://lnkd.in/dtDkPwCC
πPaper coming
π4π4π₯2β€1π₯°1
π§ 350+ Free #AI Courses by #Googleπ§
π350+ free courses from #Google to become professional in #AI & #Cloud. The full catalog (900+) includes a variety of activity: videos, documents, labs, coding, and quizzes. 15+ supported languages. No excuse.
β πππ§ππ«πππ’π―π ππ
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πReview: https://t.ly/517Dr
πFull list: https://www.cloudskillsboost.google/catalog?page=1
π350+ free courses from #Google to become professional in #AI & #Cloud. The full catalog (900+) includes a variety of activity: videos, documents, labs, coding, and quizzes. 15+ supported languages. No excuse.
β πππ§ππ«πππ’π―π ππ
β ππ§ππ«π¨ ππ¨ ππππ¬
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πReview: https://t.ly/517Dr
πFull list: https://www.cloudskillsboost.google/catalog?page=1
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π Diffutoon: new SOTA video π
πDiffutoon is a cartoon shading approach, aiming to transform photorealistic videos in anime styles. It can handle exceptionally high resolutions and rapid motions. Source code released!
πReview https://t.ly/sim2O
πPaper https://lnkd.in/dPcSnAUu
πCode https://lnkd.in/d9B_dGrf
πProject https://lnkd.in/dpcsJcX2
πDiffutoon is a cartoon shading approach, aiming to transform photorealistic videos in anime styles. It can handle exceptionally high resolutions and rapid motions. Source code released!
πReview https://t.ly/sim2O
πPaper https://lnkd.in/dPcSnAUu
πCode https://lnkd.in/d9B_dGrf
πProject https://lnkd.in/dpcsJcX2
π₯19β€3π€―3π1π₯°1π€©1π©1πΎ1
π₯ RANSAC -> PARSAC (neural) π₯
πNeural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homographies (H) at the speed of light! Source Code released π
πReview https://t.ly/r9ngg
πPaper https://lnkd.in/dadQ4Qec
πCode https://lnkd.in/dYp6gADd
πNeural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homographies (H) at the speed of light! Source Code released π
πReview https://t.ly/r9ngg
πPaper https://lnkd.in/dadQ4Qec
πCode https://lnkd.in/dYp6gADd
β€14π3β‘1π₯°1π1
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βοΈ SEELE: "moving" the subjects β‘οΈ
πSubject repositioning: manipulating an input image to reposition one of its subjects to a desired location while preserving the imageβs fidelity. SEELE is a single diffusion model to address this novel generative sub-tasks
πReview https://t.ly/4FS4H
πPaper arxiv.org/pdf/2401.16861.pdf
πProject yikai-wang.github.io/seele/
πSubject repositioning: manipulating an input image to reposition one of its subjects to a desired location while preserving the imageβs fidelity. SEELE is a single diffusion model to address this novel generative sub-tasks
πReview https://t.ly/4FS4H
πPaper arxiv.org/pdf/2401.16861.pdf
πProject yikai-wang.github.io/seele/
π20β€3π€―3π1
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π ADΞER: Event-Camera Suite π
πADΞER: a novel/unified framework for event-based video. Encoder / transcoder / decoder for ADΞER (Address, Decimation, Ξt Event Representation) video streams. Source code (RUST) released π
πReview https://t.ly/w5_KC
πPaper arxiv.org/pdf/2401.17151.pdf
πRepo github.com/ac-freeman/adder-codec-rs
πADΞER: a novel/unified framework for event-based video. Encoder / transcoder / decoder for ADΞER (Address, Decimation, Ξt Event Representation) video streams. Source code (RUST) released π
πReview https://t.ly/w5_KC
πPaper arxiv.org/pdf/2401.17151.pdf
πRepo github.com/ac-freeman/adder-codec-rs
β€7π3π₯°1
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π¦(add) Anything in Any Videoπ¦
π XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released π
πReview https://t.ly/UYhl0
πCode https://lnkd.in/gyi7Dhkn
πPaper https://lnkd.in/gXyAJ6GZ
πProject https://lnkd.in/gVA5vduD
π XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released π
πReview https://t.ly/UYhl0
πCode https://lnkd.in/gyi7Dhkn
πPaper https://lnkd.in/gXyAJ6GZ
πProject https://lnkd.in/gVA5vduD
π₯12π€―6π5π₯°1
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π¬ ABS: SOTA collision-free π¬
πABS (Agile But Safe): learning-based control framework for agile and collision-free locomotion for quadrupedal robot. Source Code announced (coming) π
πReview https://t.ly/AYu-Z
πPaper arxiv.org/pdf/2401.17583.pdf
πProject agile-but-safe.github.io/
πRepo github.com/LeCAR-Lab/ABS
πABS (Agile But Safe): learning-based control framework for agile and collision-free locomotion for quadrupedal robot. Source Code announced (coming) π
πReview https://t.ly/AYu-Z
πPaper arxiv.org/pdf/2401.17583.pdf
πProject agile-but-safe.github.io/
πRepo github.com/LeCAR-Lab/ABS
π11π3π1π₯°1