Search Results for author:
Found 5 papers, 2 papers with code
Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation
We find that shortcut learning is the root cause: the agent learns to navigate to target objects, by simply searching for the associated wall color of the target object's room.
Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling
For object detection, it is possible to view the prediction of bounding boxes as a reverse diffusion process.
Spot What Matters: Learning Context Using Graph Convolutional Networks for Weakly-Supervised Action Detection
We argue that several actions are characterized by their context, such as relevant objects and actors present in the video.
Independent Prototype Propagation for Zero-Shot Compositionality
Next we propagate the independent prototypes through a compositional graph, to learn compositional prototypes of novel attribute-object combinations that reflect the dependencies of the target distribution.
The Distribution Family of Similarity Distances
This fundamental insight opens new directions in the assessment of feature similarity, with projected improvements in object and scene recognition algorithms.
