DKT is a foundation model for transparent-object, in-the-wild, and arbitrary-length video depth and normal estimation. It repurposes video diffusion priors to achieve robust and temporally coherent perception for challenging real-world scenarios involving glass, plastic, and metal materials.

Paper | Project Page | GitHub

Transparent objects pose a significant challenge for traditional perception systems due to refraction and reflection. DKT leverages modern video diffusion models that have internalized optical rules, using lightweight LoRA adapters to predict depth and normals. It yields temporally consistent predictions for arbitrary-length input videos and achieves state-of-the-art results on benchmarks like ClearPose and DREDS.

To use this model, please follow the installation instructions in the official GitHub repository.