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Creating an Implicit Upsampler in FeatUp using the Depth-Anything model

Posted last month

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Featup is a new library for "A Model-Agnostic Framework for Features at Any Resolution"

Featup can upres the output from an AI model like DINO v2 and ResNet. I want someone that can use FeatUP to Fit an Implicit Upsampler to an Image (https://github.com/mhamilton723/FeatUp#fitting-an-implicit-upsampler-to-an-image).

Train an implicit upsampler for the Depth Anything (Depth-Anything-Large) model. Once this is done, an image can be run through FeatUP using the Depth Anything model to obtain a more detailed depth map resolution than is available in Depth-Anything-Large alone.

I am looking for someone who fully understands the assignment and not someone who can figure it out as they go.

For deliverables, I need a script that compares the output from the base Depth-Anything-Large model to the output of the Depth-Anything-Large model being run through the implicit upsampler built by FeatUP. I am expecting to see more detail in the depth map generated through FeatUP

I will consider the job complete when I have the featup model and a script to use it. I would also like to see before and afters and how long each took to infer. I need to confirm I can get it running on my side before the project will be complete. I will be running the model on 4090s, 3090s, a6000s, and A100

Activity on this job
  • Proposals:
    Less than 5
  • Last viewed by client:
    last month
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About the client
Member since Apr 6, 2022
  • United States
    Fort Lee 11:16 PM
  • 27 jobs posted
    60% hire rate, 1 open job
  • $50K total spent
    23 hires, 8 active
  • $35.82 /hr avg hourly rate paid
    876 hours
  • Tech & IT
    Small company (2-9 people)
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