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[CVPR'24 Oral] Official repository of Point Transformer V3 (PTv3)
High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
[CVPR 2025] Official repository for "Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders"
Official repo for paper "Structured 3D Latents for Scalable and Versatile 3D Generation" (CVPR'25 Spotlight).
Pointcept: a codebase for point cloud perception research. Latest works: Sonata (CVPR'25 Highlight), PTv3 (CVPR'24 Oral), PPT (CVPR'24), MSC (CVPR'23)
[CVPR 2024 Highlight] XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies
Release for Improved Denoising Diffusion Probabilistic Models
3D Dental surface segmentation with Tooth Group Network
Finetuning CLIP using LORA for Turkish language
Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation
Python implementation of some basic machine learning related algorithms
Easily train a good VC model with voice data <= 10 mins!
Source code for "Progressive Transformers for End-to-End Sign Language Production" (ECCV 2020)
a text-to-gloss-to-pose-to-video pipeline for spoken to signed language translation
Documentation and background of sign language processing
TFDS data loaders for sign language datasets.
Generate 3D objects conditioned on text or images
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionne…
Pytorch package to compute Chamfer distance between point sets (pointclouds).
Loss function Package Tensorflow Keras PyTOrch
Official implementation of the Generalized Wasserstein Dice Loss in PyTorch
2nd place solution for Xview2 challenge https://xview2.org/
pix2pix3D: Generating 3D Objects from 2D User Inputs
PyTorch implementation of YOLOv5, YOLOv6, YOLOv7, YOLOv8, Sort, StrongSort, OcSort, ByteTrack, Norfair
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
My small cheatsheets for data science, ML, computer science and more.
A playbook for systematically maximizing the performance of deep learning models.