The project proposes representing any video in 4D through trajectory fields, enabling reconstruction of dynamic scenes with temporal and spatial understanding. It builds on the Depth Anything foundation model family and uses neural network-based approaches to track and predict point trajectories across video frames. The method supports generating novel views and temporal reconstructions from input video sequences.