Tracklet[1] is a novel method for optimizing tracklet consistency, which directly takes the prediction errors into account. There are some details of reading and implementing it.

FFT(Flow-Fuse Tracker)[1] is an end-to-end DNN tracking approach, that jointly learns both target motions and associations for MOT(multiple object tracking). There are some details of reading and implementing it.

JRMOT[1] is a novel 3D MOT system that integrates information from 2D RGB images and 3D point clouds into a real-time performing framework. There are some details of reading and implementing it.

Pose-Assisted Multi-Camera Collaboration System[1] is a novel method, which enables a camera to cooperate with the others by sharing camera poses for AOT(active object tracking). There are some details of reading and implementing it.

GlobalTrack[1] is a pure global tracker for long-term tracking, without temporal consistency assumption making cumulative errors. There are some details of reading and implementing it.

SiamMask[1] is used to detect and segment objects from videos in each frame, initializing a single bounding box and outputing binary segmentation mask and rotated objects boxes. There are some details of reading and implementing it.

Tracktor[1] is used to detect objects from videos in each frame, while forming tracks by linking corresponding detections across time. There are some details of reading and implementing it.

Faster R-CNN[1] is used to detect objects in images, with outputing bounding box and class scores. There are some details of reading and implementing it.

ResNet[1] is used to classify images with deep residual learning. There are some details of reading and implementing it.

GoogLeNet[1] is used to classify images with inception v1. There are some details of reading and implementing it.