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Found 8 papers, 5 papers with code
Latent Guard: a Safety Framework for Text-to-image Generation
Hence, we propose Latent Guard, a framework designed to improve safety measures in text-to-image generation.
Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization
To mitigate this issue, we propose Bootstrapped Preference Optimization (BPO), which conducts preference learning with datasets containing negative responses bootstrapped from the model itself.
Ranked #29 on
Visual Question Answering
on MM-Vet
The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
Our model starts with two separate pathways: an appearance pathway that outputs feature-based region segmentation for a single image, and a motion pathway that outputs motion features for a pair of images.
Ranked #7 on
Unsupervised Object Segmentation
on FBMS-59
3D Shape Reconstruction from Free-Hand Sketches
Additionally, we propose a sketch standardization module to handle different sketch distortions and styles.
Unsupervised Sketch-to-Photo Synthesis
Humans can envision a realistic photo given a free-hand sketch that is not only spatially imprecise and geometrically distorted but also without colors and visual details.
CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions
Yet there has been evidence that current benchmark datasets suffer from bias, and current state-of-the-art models cannot be easily evaluated on their intermediate reasoning process.
Ranked #1 on
Referring Expression Segmentation
on CLEVR-Ref+
Using Deep Learning Method for Classification: A Proposed Algorithm for the ISIC 2017 Skin Lesion Classification Challenge
The models are built on the source images are using the Caffe [4] framework.
