Depth Anything
Unleashing the Power of Large-Scale Unlabeled Data

[Paper] [Code] [Demo]

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🔮 Awesome AI Agents

New 🌟 Curated list of AI agents 🌟 !.

▪ 150+ AI agents and frameworks.
▪ Filter by usage scenarios .
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[ZeroToMastery] PyTorch for Deep Learning

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🖥 Depth Anything is now available

Monocular depth estimation is the task of estimating the depth value (distance relative to the camera) of each pixel given a single (monocular) RGB image.

🖥 Code: https://github.com/NielsRogge/Transformers-Tutorials/blob/master/Depth%20Anything/Predicting_depth_in_an_image_with_Depth_Anything.ipynb

🚀 HF: https://huggingface.co/docs/transformers/v4.28.0/tasks/monocular_depth_estimation

📚 Paper: https://huggingface.co/papers/2401.10891

List of important courses available on our channel “Course Portfolio”

Note: We are adding more courses daily

🟢 [Coursera] Data Wrangling With Python Specialization

🟢 [Coursera] Machine Learning On Google Cloud Specialization

🟢 [ZeroToMastery] PyTorch for Deep Learning.

🟢 [Academind Pro] Python Django – The Practical Guide

🟢 [O’REILLY] Learn AI-Assisted Python Programming

🟢 Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

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🟢 [Coursera] Data Structures And Algorithms Specialization

🟢 [Udacity] Data Structures And Algorithms Nanodegree v2.0.0

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CreativeSynth: Creative Blending and Synthesis of Visual Arts based on Multimodal Diffusion

🖥 Github: https://github.com/haha-lisa/creativesynth

📕 Paper: https://arxiv.org/pdf/2401.14066v1.pdf

✨ Tasks: https://paperswithcode.com/task/image-generation

pix2gestalt: Amodal Segmentation by Synthesizing Wholes

🖥 Github: https://github.com/cvlab-columbia/pix2gestalt

📕 Paper: https://arxiv.org/pdf/2401.14398v1.pdf

✨ Tasks: https://paperswithcode.com/task/3d-reconstruction

⭐️ GALA: Generating Animatable Layered Assets
from a Single Scan

🖥 Code: https://github.com/snuvclab/GALA

🚀 Project: snuvclab.github.io/gala

📚 Paper: https://arxiv.org/abs/2401.12979

⚡️ DiffSynth Studio

🖥 Code: https://github.com/Artiprocher/DiffSynth-Studio

🚀 Project: https://ecnu-cilab.github.io/DiffutoonProjectPage/

📚 Paper: https://arxiv.org/pdf/2401.16224.pdf

DVT

🖥 Github: https://github.com/zhangzm0128/DVT

📕 Paper: https://www.ieee-jas.net/en/article/id/ec6a16fa-d348-417a-af0f-dd734c60439c

🔥Datasets: https://paperswithcode.com/dataset/cifar-10

✨ Tasks: https://paperswithcode.com/task/image-classification

📷 InstructIR: High-Quality Image Restoration Following Human Instructions

🖥 Code: https://github.com/mv-lab/InstructIR

🚀 Project: mv-lab.github.io/InstructIR/

🎮 Colab: https://colab.research.google.com/drive/1OrTvS-i6uLM2Y8kIkq8ZZRwEQxQFchfq

📚 Paper: https://arxiv.org/abs/2401.16468

⚡️ MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

🖥 Code: https://github.com/PKU-YuanGroup/MoE-LLaVA

🚀 Jupyter: https://github.com/camenduru/MoE-LLaVA-jupyter

📚 Paper: https://arxiv.org/abs/2401.15947

⚡️ MotionDirector: Motion Customization of Text-to-Video Diffusion Models

🖥 Github: https://github.com/showlab/MotionDirector

📕 Paper: https://arxiv.org/abs/2310.08465

⭐️ Project: showlab.github.io/MotionDirector/

Vaccine: Perturbation-aware Alignment for Large Language Model

🖥 Github: https://github.com/git-disl/vaccineT

📕 Paper: https://arxiv.org/pdf/2402.01109v1.pdf

🔥Datasets: https://paperswithcode.com/dataset/sst

✨ Tasks: https://paperswithcode.com/task/language-modelling

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🏆 DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

🌐 page: https://doubiiu.github.io/projects/DynamiCrafter

📄 paper: https://arxiv.org/abs/2310.12190

🧬 code: https://github.com/Doubiiu/DynamiCrafter

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