Transformation of extrinsic camera parameters from solvePnP

Question

I have a camera that has known intrinsic parameters but unknown extrinsic parameters. I am attempting to get an extrinsic calibration and to do that, I positioned a chessboard pattern with known world coordinates in the frame of the camera. To get the extrinsic calibration, I am comparing two OpenCV methods from the Calib3D module:

val flags = CALIB_USE_INTRINSIC_GUESS or
    CALIB_FIX_PRINCIPAL_POINT or
    CALIB_FIX_FOCAL_LENGTH or
    CALIB_FIX_K1 or
    CALIB_FIX_K2 or
    CALIB_FIX_K3 or
    CALIB_FIX_K4 or
    CALIB_FIX_K5 or
    CALIB_FIX_K6 or
    CALIB_FIX_S1_S2_S3_S4 or
    CALIB_FIX_TAUX_TAUY
val overallRms = Calib3d.calibrateCamera(
    objectPoints,
    imagePoints,
    imageSize,
    cameraMatrix,
    distortionCoefficients,
    rotationVectors,
    translationVectors,
    flags
)

and

val solveReturnValue = Calib3d.solvePnP(
    objectPointsInFrame.second,
    imagePointsInFrame.second,
    cameraMatrix,
    distortionCoefficients,
    rotationVector,
    translationVector,
    false // useExtrinsicsGuess
)

Both methods yield the same results for translation and rotation +- 1.5 units. However, I have read on multiple occasions (e.g., here ) that solvePnP yields the inverse of calibrateCamera and one needs to invert the transformation again by

1. computing the rotation matrix R from the rotation vector using Calib3D.Rodrigues()
2. inverting the rotation by inverting the rotation matrix
3. inverting the translation using -R.t()*tvec

which according to my testing does not seem to be the case. Hence, my questions: Is it safe to assume that rotationVectors and translationVectors are the extrinsic calibration of the camera? And when is the aforementioned transformation actually necessary?