1st place solution (Team StylingAI Inc. & PKU AIIC) for CVPR 2020 DeepFashion2 Clothes Landmark Detection Track. Aggregation and Finetuning for Clothes Landmark Detection

A supervised Deep Learning approach to clothing instance segmentation with Mask R-CNN

fashion segmentation & classification project with Mask R-CNN

Web app and fashion detection/recommendation engine that leverages deep learning, computer vision, and LLM's to provide outfit recommendations.

A companion repo to my work done in Cybint

A full implementation of clothing detection, instance segmentation, and classification using Mask R-CNN on the DeepFashion2 dataset. Features include detection of 13 clothing categories, individual item extraction, batch processing, and a Flask-based REST API. Optimized for GPUs with 4GB+ VRAM and pre-trained on COCO for fast transfer learning.

Implement clothing detection, segmentation, and classification using Mask R-CNN on the DeepFashion2 dataset for precise garment extraction.

Smart AI Fashion Stylist that detects outfit types, analyzes color palettes, and recommends complementary clothing using DeepFashion2, CLIP, and ResNet50.

ROIs calibration/alignment on trousers with deep learning-based keypoint detection.