TSDM[1] is a RGB-D tracker which use depth information to pretreatment and fuse information to pro-processing. It is composed of a Mask-generator(M-g), SiamRPN++ and a Depth-refiner(D-r). There are some details of reading and implementing it.

Image Transformer[1] is a sequence modeling formulation of image generation generalized by Transformer, which restricting the self-attention mechanism to attend to local neighborhoods, while maintaining large receptive field. There are some details of reading and implementing it.

SiamRPN++[1] is a novel Siamese network based tracker to adopt deep networks that broke strict translation invariance. It performs layer-wise and depth-wise aggregations to successfully trained a ResNet-driven Siamese tracker. There are some details of reading and implementing it.

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.