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Based on your experience in your updated answer I would intuitively say that the noise parameter of your odometry is off. So you would need to tune your Kalman filter. The tuning parameters of a Kalman filter are process and observation noise levels (assuming your model is correct and can be simplified well enough as having gaussian noise).
Could you try and increase the process noise level of the odometry? Because you don't want the filter to drift between measurement updates (of your visual pose), it should always yield the best possible estimate. I don't know the package, so I can't tell you exactly where to change the parameters.
Remember: tuning a kalman filter can be tedious..
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