FastViT is a high-performance hybrid vision transformer designed to deliver exceptional speed and accuracy—especially on resource-constrained platforms like mobile phones…
Object Detection
YOLOv9: Train-from-Scratch Object Detection That Beats Pretrained Models with Programmable Gradient Information 9391
YOLOv9 marks a significant leap forward in real-time object detection by directly confronting a long-standing but often overlooked problem in…
GhostNet: High-Accuracy Vision Models with Minimal Compute for Edge Deployment 4355
Overview Deploying powerful computer vision models on resource-constrained devices—such as smartphones, IoT sensors, or drones—has long been a major engineering…
detrex: A Unified, Modular Benchmark for Detection Transformers—Accelerate Object Detection, Segmentation, and Pose Estimation Research 2250
If you’re evaluating object detection frameworks for a new computer vision project, you’ve likely encountered the rise of DETR (Detection…
D-FINE: Real-Time Object Detection with DETR-Level Accuracy and No Inference Overhead 2756
Object detection has long faced a fundamental trade-off: high accuracy or real-time speed—but rarely both. Enter D-FINE, a breakthrough real-time…
AM-RADIO: Unify Vision Foundation Models into One High-Performance Backbone for Multimodal, Segmentation, and Detection Tasks 1357
In modern computer vision, practitioners often juggle multiple foundation models—CLIP for vision-language alignment, DINOv2 for dense feature extraction, and SAM…
CARAFE: Boost Dense Prediction Accuracy with Content-Aware, Lightweight Feature Upsampling 32164
Feature upsampling is a critical but often overlooked component in modern computer vision pipelines. Whether you’re building an object detector,…
PP-PicoDet: Real-Time Object Detection with SOTA Accuracy on Mobile and Edge Devices 13974
In today’s era of intelligent edge computing, deploying high-performance computer vision models on resource-constrained devices like smartphones, embedded sensors, and…