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Found 5 papers, 1 papers with code
Conditional Tuning Network for Few-Shot Adaptation of Segmentation Anything Model
CAT-SAM freezes the entire SAM and adapts its mask decoder and image encoder simultaneously with a small number of learnable parameters.
Estimating 3D Uncertainty Field: Quantifying Uncertainty for Neural Radiance Fields
To quantify the uncertainty on the learned surface, we model a stochastic radiance field.
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds
In addition, we design a domain randomization technique that alternatively randomizes the geometry styles of point clouds and aggregates their embeddings, ultimately leading to a generalizable model that can improve 3DSS under various adverse weather effectively.
Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision
We show that training our network solely with synthetic data and the proposed DA yields results competitive with models trained on real data.
Multi-agent Interactive Prediction under Challenging Driving Scenarios
In order to drive safely on the road, autonomous vehicle is expected to predict future outcomes of its surrounding environment and react properly.
