I am not passing the image_mean and Image_std manually.
Sure, this is how I am calling the model:
images,targets = next(iter(trainloader))
images = list(torch.squeeze(image) for image in images) 
print(len(images))                                      // Will output 431
print(images[0].shape)                              // Will output torch.size[3,256,320]

targets = [{k: v for k, v in t.items()} for t in targets]
print(len(targets))                                     // Will output 431

output = model(images,targets)

Here 431 is the number of frames in my first video. Targets contains the bounding box coordinates, masks and image ids for each individual frame. It is a list of dictionaries. I hope that this is fine?