python demo.py --cfg experiments/dff_rfcn/cfgs/resnet_v1_101_flownet_imagenet_vid_rfcn_end2end_ohem.yaml --video 0guogcfcb4q156ug2eqlg_source.mp4 Use code with caution. Copied to clipboard Feature Extraction Logic Keyframes ( Ikcap I sub k
): The model runs a full forward pass through the feature network ( Nfeatcap N sub f e a t end-sub ) to get feature maps A lightweight FlowNet ( Nflowcap N sub f l o w end-sub ) calculates the displacement field ( Mi→kcap M sub i right arrow k end-sub ) between the current frame and the last keyframe. 0guogcfcb4q156ug2eqlg_source.mp4
The deep features are propagated using a bilinear warping function: python demo