ORK replacement package?

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Hi, ORK looks dead, and so I was thinking to switch to another 3D object recognition package. I saw this same question but it's 8 years old, so I ask again.

I have identified so far plenty of ROS packages that recognize objects from 2D images, and some of them complement it with depth from a 3D camera:

• RAIL_segmentation segments pointclouds like tabletop, but cannot (afaik) recognize
• RAIL object detector detects objects in 2D using YOLOv2 or DRFCN , no 3D info
• find_object_2d 2D w/ OpenCV but adds 3D pose with 3D camera
• ros-openvino-toolkit Intel’s ROS wrapper for OpenVINO: 2D CNN-based obj. rec; no 3D info
• ros_openvino Same but from one guy
• YOLO perception Looks very active; no 3D info
• ros_people_object_detection_tensorflow similar to YOLO but adds 3D info
• ros_object_analytics detect and tracking, uses GPU
• object-recognition-node-with-monocular-camera-package uses OpenCV’s DNN
• ...

But pretty sure there are more (and even more will soon appear). Looks like most approaches now involve 2D object recognition using Deep Learning and then add depth by locating the object centroid in a depth image. Am I right? Mesh-matching times are gone?

What I want is, as with ORK, tabletop segmentation and recognition of the objects on the table, with 3D pose, to run a demo like that on this video. Has anyone any clue about which package looks best place to become a new "de facto" standard, or at least continue with active maintaining for the mid-term?

Thanks a lot!

UPDATE I have found another similar question, though I keep mine as it's more detailed.