Transformer Encoder Decoder Object Prediction

via “transformer encoder-decoder with learned object queries for set prediction”

object-detection model by undefined. 2,28,520 downloads.

Unique: Uses learned object query embeddings (not spatial grids or anchors) that attend to the full feature map via multi-head cross-attention, enabling the model to dynamically allocate detection capacity based on image content rather than predefined spatial locations

vs others: More flexible than anchor-based methods (no anchor tuning) and more interpretable than dense prediction heads; weaker than specialized small-object detectors due to set prediction formulation