1. A method of forecasting multiple positions of a subject depicted by an image, the method comprising: receiving, by a forecasting neural network, an image depicting a subject, wherein the forecasting neural network comprises an encoder neural network, a recurrent neural network, and a decoder neural network; extracting, by the encoder neural network, a feature of the received image; providing the extracted feature to the recurrent neural network; determining, by the recurrent neural network, a first modification to the extracted feature; determining, by the recurrent neural network and based on the first modification, a second modification to the extracted feature; generating, by the recurrent neural network, a first forecasted feature based on the determined first modification and a second forecasted feature based on the determined second modification; providing the first forecasted feature and the second forecasted feature to the decoder neural network; and generating, by the decoder neural network, a first set of keypoints and a second set of keypoints, wherein each keypoint in the first set of keypoints indicates a forecasted position of a respective portion of the image subject and each keypoint in the second set of keypoints indicates a second forecasted position of the respective portion of the image subject.