diff --git a/modules/calib3d/include/opencv2/calib3d.hpp b/modules/calib3d/include/opencv2/calib3d.hpp
index 61e3aca810..fd35b7d5f3 100644
--- a/modules/calib3d/include/opencv2/calib3d.hpp
+++ b/modules/calib3d/include/opencv2/calib3d.hpp
@@ -2492,13 +2492,13 @@ CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
 
 @param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should
 be floating-point (single or double precision).
-@param points2 Array of the second image points of the same size and format as points1 .
+@param points2 Array of the second image points of the same size and format as points1.
 @param cameraMatrix Camera intrinsic matrix \f$\cameramatrix{A}\f$ .
 Note that this function assumes that points1 and points2 are feature points from cameras with the
-same camera intrinsic matrix. If this assumption does not hold for your use case, use
-#undistortPoints with `P = cv::NoArray()` for both cameras to transform image points
-to normalized image coordinates, which are valid for the identity camera intrinsic matrix. When
-passing these coordinates, pass the identity matrix for this parameter.
+same camera intrinsic matrix. If this assumption does not hold for your use case, use another
+function overload or #undistortPoints with `P = cv::NoArray()` for both cameras to transform image
+points to normalized image coordinates, which are valid for the identity camera intrinsic matrix.
+When passing these coordinates, pass the identity matrix for this parameter.
 @param method Method for computing an essential matrix.
 -   @ref RANSAC for the RANSAC algorithm.
 -   @ref LMEDS for the LMedS algorithm.
@@ -2590,23 +2590,13 @@ Mat findEssentialMat(
 
 @param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should
 be floating-point (single or double precision).
-@param points2 Array of the second image points of the same size and format as points1 .
-@param cameraMatrix1 Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
-Note that this function assumes that points1 and points2 are feature points from cameras with the
-same camera matrix. If this assumption does not hold for your use case, use
-#undistortPoints with `P = cv::NoArray()` for both cameras to transform image points
-to normalized image coordinates, which are valid for the identity camera matrix. When
-passing these coordinates, pass the identity matrix for this parameter.
-@param cameraMatrix2 Camera matrix \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
-Note that this function assumes that points1 and points2 are feature points from cameras with the
-same camera matrix. If this assumption does not hold for your use case, use
-#undistortPoints with `P = cv::NoArray()` for both cameras to transform image points
-to normalized image coordinates, which are valid for the identity camera matrix. When
-passing these coordinates, pass the identity matrix for this parameter.
-@param distCoeffs1 Input vector of distortion coefficients
+@param points2 Array of the second image points of the same size and format as points1.
+@param cameraMatrix1 Camera matrix for the first camera \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param cameraMatrix2 Camera matrix for the second camera \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs1 Input vector of distortion coefficients for the first camera
 \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
 of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
-@param distCoeffs2 Input vector of distortion coefficients
+@param distCoeffs2 Input vector of distortion coefficients for the second camera
 \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
 of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
 @param method Method for computing an essential matrix.