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Abhaykoulย 
posted an update 5 days ago
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1480
๐Ÿ”ฅ BIG ANNOUNCEMENT: THE HELPINGAI API IS LIVE! ๐Ÿ”ฅ

Yo, the moment youโ€™ve all been waiting for is here! ๐Ÿš€ The HelpingAI API is now LIVE and ready to level up your projects! ๐Ÿ”ฅ Weโ€™re bringing that next-level AI goodness straight to your fingertips. ๐Ÿ’ฏ

No more waitingโ€” itโ€™s time to build something epic! ๐Ÿ™Œ

From now on, you can integrate our cutting-edge AI models into your own applications, workflows, and everything in between. Whether youโ€™re a developer, a creator, or just someone looking to make some serious moves, this is your chance to unlock the full potential of emotional intelligence and adaptive AI.

Check out the docs ๐Ÿ”ฅ and letโ€™s get to work! ๐Ÿš€

๐Ÿ‘‰ Check out the docs and start building (https://helpingai.co/docs)
๐Ÿ‘‰ Visit the HelpingAI website (https://helpingai.co/)
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yanghengย 
updated a Space 18 days ago
DmitryRyuminย 
posted an update 3 months ago
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2606
๐Ÿ”ฅ๐ŸŽญ๐ŸŒŸ New Research Alert - HeadGAP (Avatars Collection)! ๐ŸŒŸ๐ŸŽญ๐Ÿ”ฅ
๐Ÿ“„ Title: HeadGAP: Few-shot 3D Head Avatar via Generalizable Gaussian Priors ๐Ÿ”

๐Ÿ“ Description: HeadGAP introduces a novel method for generating high-fidelity, animatable 3D head avatars from few-shot data, using Gaussian priors and dynamic part-based modelling for personalized and generalizable results.

๐Ÿ‘ฅ Authors: @zxz267 , @walsvid , @zhaohu2 , Weiyi Zhang, @hellozhuo , Xu Chang, Yang Zhao, Zheng Lv, Xiaoyuan Zhang, @yongjie-zhang-mail , Guidong Wang, and Lan Xu

๐Ÿ“„ Paper: HeadGAP: Few-shot 3D Head Avatar via Generalizable Gaussian Priors (2408.06019)

๐ŸŒ Github Page: https://headgap.github.io

๐Ÿš€ CVPR-2023-24-Papers: https://github.com/DmitryRyumin/CVPR-2023-24-Papers

๐Ÿš€ WACV-2024-Papers: https://github.com/DmitryRyumin/WACV-2024-Papers

๐Ÿš€ ICCV-2023-Papers: https://github.com/DmitryRyumin/ICCV-2023-Papers

๐Ÿ“š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin

๐Ÿš€ Added to the Avatars Collection: DmitryRyumin/avatars-65df37cdf81fec13d4dbac36

๐Ÿ” Keywords: #HeadGAP #3DAvatar #FewShotLearning #GaussianPriors #AvatarCreation #3DModeling #MachineLearning #ComputerVision #ComputerGraphics #GenerativeAI #DeepLearning #AI
DmitryRyuminย 
posted an update 3 months ago
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2047
๐Ÿš€๐Ÿ•บ๐ŸŒŸ New Research Alert - ECCV 2024 (Avatars Collection)! ๐ŸŒŸ๐Ÿ’ƒ๐Ÿš€
๐Ÿ“„ Title: Expressive Whole-Body 3D Gaussian Avatar ๐Ÿ”

๐Ÿ“ Description: ExAvatar is a model that generates animatable 3D human avatars with facial expressions and hand movements from short monocular videos using a hybrid mesh and 3D Gaussian representation.

๐Ÿ‘ฅ Authors: Gyeongsik Moon, Takaaki Shiratori, and @psyth

๐Ÿ“… Conference: ECCV, 29 Sep โ€“ 4 Oct, 2024 | Milano, Italy ๐Ÿ‡ฎ๐Ÿ‡น

๐Ÿ“„ Paper: MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos (2407.08414)

๐Ÿ“„ Paper: Expressive Whole-Body 3D Gaussian Avatar (2407.21686)

๐ŸŒ Github Page: https://mks0601.github.io/ExAvatar
๐Ÿ“ Repository: https://github.com/mks0601/ExAvatar_RELEASE

๐Ÿš€ CVPR-2023-24-Papers: https://github.com/DmitryRyumin/CVPR-2023-24-Papers

๐Ÿš€ WACV-2024-Papers: https://github.com/DmitryRyumin/WACV-2024-Papers

๐Ÿš€ ICCV-2023-Papers: https://github.com/DmitryRyumin/ICCV-2023-Papers

๐Ÿ“š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin

๐Ÿš€ Added to the Avatars Collection: DmitryRyumin/avatars-65df37cdf81fec13d4dbac36

๐Ÿ” Keywords: #ExAvatar #3DAvatar #FacialExpressions #HandMotions #MonocularVideo #3DModeling #GaussianSplatting #MachineLearning #ComputerVision #ComputerGraphics #DeepLearning #AI #ECCV2024
DmitryRyuminย 
posted an update 3 months ago
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1854
๐Ÿ”ฅ๐ŸŽญ๐ŸŒŸ New Research Alert - ECCV 2024 (Avatars Collection)! ๐ŸŒŸ๐ŸŽญ๐Ÿ”ฅ
๐Ÿ“„ Title: MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos ๐Ÿ”

๐Ÿ“ Description: MeshAvatar is a novel pipeline that generates high-quality triangular human avatars from multi-view videos, enabling realistic editing and rendering through a mesh-based approach with physics-based decomposition.

๐Ÿ‘ฅ Authors: Yushuo Chen, Zerong Zheng, Zhe Li, Chao Xu, and Yebin Liu

๐Ÿ“… Conference: ECCV, 29 Sep โ€“ 4 Oct, 2024 | Milano, Italy ๐Ÿ‡ฎ๐Ÿ‡น

๐Ÿ“„ Paper: MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos (2407.08414)

๐ŸŒ Github Page: https://shad0wta9.github.io/meshavatar-page
๐Ÿ“ Repository: https://github.com/shad0wta9/meshavatar

๐Ÿ“บ Video: https://www.youtube.com/watch?v=Kpbpujkh2iI

๐Ÿš€ CVPR-2023-24-Papers: https://github.com/DmitryRyumin/CVPR-2023-24-Papers

๐Ÿš€ WACV-2024-Papers: https://github.com/DmitryRyumin/WACV-2024-Papers

๐Ÿš€ ICCV-2023-Papers: https://github.com/DmitryRyumin/ICCV-2023-Papers

๐Ÿ“š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin

๐Ÿš€ Added to the Avatars Collection: DmitryRyumin/avatars-65df37cdf81fec13d4dbac36

๐Ÿ” Keywords: #MeshAvatar #3DAvatars #MultiViewVideo #PhysicsBasedRendering #TriangularMesh #AvatarCreation #3DModeling #NeuralRendering #Relighting #AvatarEditing #MachineLearning #ComputerVision #ComputerGraphics #DeepLearning #AI #ECCV2024
Abhaykoulย 
posted an update 4 months ago
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2908
Introducing HelpingAI2-9B, an emotionally intelligent LLM.
Model Link : https://huggingface.co./OEvortex/HelpingAI2-9B
Demo Link: Abhaykoul/HelpingAI2

This model is part of the innovative HelpingAI series and it stands out for its ability to engage users with emotional understanding.

Key Features:
-----------------

* It gets 95.89 score on EQ Bench greather than all top notch LLMs, reflecting advanced emotional recognition.
* It gives responses in empathetic and supportive manner.

Must try our demo: Abhaykoul/HelpingAI2
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DmitryRyuminย 
posted an update 5 months ago
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2300
๐Ÿš€๐Ÿ•บ๐ŸŒŸ New Research Alert - CVPR 2024 (Avatars Collection)! ๐ŸŒŸ๐Ÿ’ƒ๐Ÿš€
๐Ÿ“„ Title: IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing ๐Ÿ”

๐Ÿ“ Description: IntrinsicAvatar is a method for extracting high-quality geometry, albedo, material, and lighting properties of clothed human avatars from monocular videos using explicit ray tracing and volumetric scattering, enabling realistic animations under varying lighting conditions.

๐Ÿ‘ฅ Authors: Shaofei Wang, Boลพidar Antiฤ‡, Andreas Geiger, and Siyu Tang

๐Ÿ“… Conference: CVPR, Jun 17-21, 2024 | Seattle WA, USA ๐Ÿ‡บ๐Ÿ‡ธ

๐Ÿ”— Paper: IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing (2312.05210)

๐ŸŒ Github Page: https://neuralbodies.github.io/IntrinsicAvatar/
๐Ÿ“ Repository: https://github.com/taconite/IntrinsicAvatar

๐Ÿ“บ Video: https://www.youtube.com/watch?v=aS8AIxgVXzI

๐Ÿš€ CVPR-2023-24-Papers: https://github.com/DmitryRyumin/CVPR-2023-24-Papers

๐Ÿš€ WACV-2024-Papers: https://github.com/DmitryRyumin/WACV-2024-Papers

๐Ÿš€ ICCV-2023-Papers: https://github.com/DmitryRyumin/ICCV-2023-Papers

๐Ÿ“š More Papers: more cutting-edge research presented at other conferences in the DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin

๐Ÿš€ Added to the Avatars Collection: DmitryRyumin/avatars-65df37cdf81fec13d4dbac36

๐Ÿ” Keywords: #IntrinsicAvatar #InverseRendering #MonocularVideos #RayTracing #VolumetricScattering #3DReconstruction #MachineLearning #ComputerVision #DeepLearning #AI #CVPR2024