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A latent text-to-image diffusion model
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
High-Resolution Image Synthesis with Latent Diffusion Models
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Using Low-rank adaptation to quickly fine-tune diffusion models.
This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) fo…
NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
Diffusion attentive attribution maps for interpreting Stable Diffusion.
A SAM-based model for instance segmentation of images of grains
The open source Meme Search Engine and Finder. Free and built to self-host locally with Python, Ruby, and Docker.
Open and efficient video watermarking
A deep learning approach to predicting breast tumor proliferation scores for the TUPAC16 challenge
[NeurIPS 2023 D&B] VidChapters-7M: Video Chapters at Scale
Official repository of DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models
Faster and more precisely than Grad-CAM
DataCV2024: The 2nd DataCV Challenge in conjunction with the CVPR 2024 Visual Dataset Understanding workshop
Code to the paper "Language Imbalance Can Boost Cross-lingual Generalisation"
visionxyz / iterative_closest_point_2d_py3_opencv3
Forked from KojiKobayashi/iterative_closest_point_2dIterative Closest Point 2D with python3 and opencv3