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Showing 1 to 3 of 3 for “"Large-Vision-Models"”.

  1. Learning New Dimensions of Human Visual Similarity using Synthetic Data

    … To achieve this we use recent text-to-image models to create synthetic pairs that are perturbed along various dimensions. We observe that popular perceptual metrics fall short of explaining our new data and introduce a new metric, DreamSim, tuned to better align with human perception. We …

    mit Repository record for Learning New Dimensions of Human Visual Similarity using Synthetic Data (opens in a new tab)

  2. Hands in action: from 4D reconstruction to animation and robotics

    … is acquiring 3D data to train machine learning models for 3D prediction. Unlike 2D labels that can be obtained through human labelers, collecting 3D annotations requires extensive lab setups. These setups often constrain the interactions depending on the capture settings, thereby hindering the …

    uiuc Repository record for Hands in action: from 4D reconstruction to animation and robotics (opens in a new tab)

  3. SAMPLS: A prompt engineering approach using Segment-Anything-Model for PLant Science research

    … network model that requires training with a large amount of manually labeled confocal images and lacks generalizability. In this research, we test a foundation model called the Segment Anything Model (SAM) to evaluate its zero-shot learning capability and whether prompt engineering can reduce …

    vt Repository record for SAMPLS: A prompt engineering approach using Segment-Anything-Model for PLant Science research (opens in a new tab)