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Found 4 papers, 1 papers with code
CLIP-Count: Towards Text-Guided Zero-Shot Object Counting
Recent advances in visual-language models have shown remarkable zero-shot text-image matching ability that is transferable to down-stream tasks such as object detection and segmentation.
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Zero-Shot Counting
on FSC147
Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs
Transformer models have made tremendous progress in various fields in recent years.
Prompt-based Learning for Unpaired Image Captioning
Inspired by the success of Vision-Language Pre-Trained Models (VL-PTMs) in this research, we attempt to infer the cross-domain cue information about a given image from the large VL-PTMs for the UIC task.
Unpaired Image Captioning by Image-level Weakly-Supervised Visual Concept Recognition
The image-level labels are utilized to train a weakly-supervised object recognition model to extract object information (e. g., instance) in an image, and the extracted instances are adopted to infer the relationships among different objects based on an enhanced graph neural network (GNN).
