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Found 10 papers, 6 papers with code
Box-based Refinement for Weakly Supervised and Unsupervised Localization Tasks
It has been established that training a box-based detector network can enhance the localization performance of weakly supervised and unsupervised methods.
Zero-Shot Audio Captioning via Audibility Guidance
Instead, captioning occurs as an inference process that involves three networks that correspond to the three desired qualities: (i) A Large Language Model, in our case, for reasons of convenience, GPT-2, (ii) A model that provides a matching score between an audio file and a text, for which we use a multimodal matching network called ImageBind, and (iii) A text classifier, trained using a dataset we collected automatically by instructing GPT-4 with prompts designed to direct the generation of both audible and inaudible sentences.
Ranked #2 on
Zero-shot Audio Captioning
on AudioCaps
Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models
A major challenge in the segmentation of medical images is the large inter- and intra-observer variability in annotations provided by multiple experts.
AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder
The recently introduced Segment Anything Model (SAM) combines a clever architecture and large quantities of training data to obtain remarkable image segmentation capabilities.
Ranked #1 on
Video Polyp Segmentation
on SUN-SEG-Easy (Unseen)
Similarity Maps for Self-Training Weakly-Supervised Phrase Grounding
A phrase grounding model receives an input image and a text phrase and outputs a suitable localization map.
What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs
Moreover, training takes place in a weakly supervised setting, where no bounding boxes are provided.
End-to-End Segmentation via Patch-wise Polygons Prediction
The leading segmentation methods represent the output map as a pixel grid.
Learning a Weight Map for Weakly-Supervised Localization
In the weakly supervised localization setting, supervision is given as an image-level label.
Explainability Guided Multi-Site COVID-19 CT Classification
Radiologist examination of chest CT is an effective way for screening COVID-19 cases.
End to End Trainable Active Contours via Differentiable Rendering
We present an image segmentation method that iteratively evolves a polygon.
