You can run the micrographs through topaz denoise before manual picking. In my experience it produces micrographs that are much easier to manually pick than simple low-pass filtering, and you can often find less obvious orientations more easily.
Also note that topaz learns to distinguish particles from background by “looking” at very few pixels. This message contains relevant info, the rest you can find in the help bubbles of the topaz GUI to figure out. In the “train” section, hover the mouse over the “Particle radius” blue parameter, and it will explain that the radius in pixels around the training coordinate defines what to consider as “particle” versus “background” further away from this radius. The default value of this parameter is very small: 3 pixels. So, if I understand this correctly, it shouldn’t matter too much that you miss certain views in manual picking, as long as they have a similar pixel value distributions as other views (sufficiently different compared to the background, I suppose). Again if I understand correctly, this is why the downsampling factor is one of the most important parameters, and presumably one could compensate for insufficient downsampling by increasing the particle radius (but in terms of computational efficiency, it is better to keep the radius small and downsample more to bring the particle size in the ballpark of this small radius: this will produce smaller micrographs, which will take less time to train and pick).