3D detection pipeline filtering

Is your feature request related to a problem? Please describe.
3D detection pipeline need filtering

Describe the solution you'd like

Filtering algo, example below

        def _filter_outliers_statistical(points_array: np.ndarray, k: int = 20, std_ratio: float = 2.0) -> np.ndarray:
            if points_array.shape[0] == 0:
                return points_array
            k_eff = min(max(2, k), points_array.shape[0])
            nn = NearestNeighbors(n_neighbors=k_eff, algorithm="auto")
            nn.fit(points_array)
            distances, _ = nn.kneighbors(points_array)
            # exclude the zero-distance to self by dropping the first column when possible
            if distances.shape[1] > 1:
                mean_neighbor_distance = distances[:, 1:].mean(axis=1)
            else:
                mean_neighbor_distance = distances.mean(axis=1)
            threshold = mean_neighbor_distance.mean() + std_ratio * mean_neighbor_distance.std()
            inlier_mask = mean_neighbor_distance <= threshold
            return points_array[inlier_mask]

Describe alternatives you've considered
None