Showing 141-159 of 159 projects
An object detection framework that bridges the gap between anchor-based and anchor-free detection models.
Official implementation of an ultra-fast single-view 3D reconstruction tool built with Python.
Powerful SOTA computer vision model for various image enhancement tasks like denoising, deblurring, and more.
An AI-powered anime super-resolution tool built for developers who work with computer vision models.
PyTorch code for a CVPR 2018 paper on few-shot learning, a technique for training ML models with limited data.
Code for high-fidelity 3D human avatar modeling using animatable Gaussians, a novel approach for pose-dependent 3D reconstruction.
A Python library for depth estimation and 3D/4D reconstruction using AI-powered prompts.
A PyTorch library for training and deploying efficient computer vision models using ViT-based architectures.
A research project focused on open-world object detection using continual and contrastive learning techniques.
A CVPR 2024 and TPAMI 2025 AI-powered multimodal learning architecture for vibe coders.
Official implementation of a CVPR'25 oral paper on motion-controllable video diffusion models using real-time warped noise.
Official PyTorch implementation of a computer vision model for tracking 2D pixels in 3D space.
Official implementation of HyperStyle, a StyleGAN inversion method using hypernetworks for real image editing.
A high-quality 3D PBR asset generation tool powered by primitive diffusion models for CVPR 2025.
An open-source library for estimating optical flow, a fundamental computer vision task, using deep neural networks.
A boundary-aware face alignment algorithm for computer vision tasks, published at CVPR 2018.
An end-to-end framework for high-resolution monocular metric depth estimation, useful for computer vision applications.
Official PyTorch implementation of a CVPR 2022 paper on GAN-supervised dense visual alignment.
This Python library provides a method for removing obstructions from images, useful for AI-powered computer vision applications.
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