I have experienced a lot of stereo, ToF Cameras and also with Deep Stereo algorithms, I would say that, None of these two can surpass accuracy of Neural Stereo Depth, RAFT Stereo, High Frequency Stereo Matching Network, Stereoformer etc are the whole on another level when comparing with Classical and Mono.
Yes, totally agree. I thinkl that for some super specific cases, the plain math can be a little bit more accurate. But for 99% of real tasks, it doesn't matter.
For UniMatch I used this version - github.com/fateshelled/unimatch_onnx (original one is here - github.com/autonomousvision/unimatch ) For Depth Anything I used this one - huggingface.co/spaces/depth-anything/Depth-Anything-V2
ua-cam.com/video/24iwwksDfE4/v-deo.html - Second sample
ua-cam.com/video/YDzV87feewA/v-deo.html - First sample
I have experienced a lot of stereo, ToF Cameras and also with Deep Stereo algorithms, I would say that, None of these two can surpass accuracy of Neural Stereo Depth, RAFT Stereo, High Frequency Stereo Matching Network, Stereoformer etc are the whole on another level when comparing with Classical and Mono.
Yes, totally agree.
I thinkl that for some super specific cases, the plain math can be a little bit more accurate.
But for 99% of real tasks, it doesn't matter.
Please, could you add the links to the models? or papers?
For UniMatch I used this version - github.com/fateshelled/unimatch_onnx (original one is here - github.com/autonomousvision/unimatch )
For Depth Anything I used this one - huggingface.co/spaces/depth-anything/Depth-Anything-V2