Dream the impossible: Outlier imagination with diffusion models
Utilizing auxiliary outlier datasets to regularize the machine learning model has
demonstrated promise for out-of-distribution (OOD) detection and safe prediction. Due to the …
demonstrated promise for out-of-distribution (OOD) detection and safe prediction. Due to the …
Detector guidance for multi-object text-to-image generation
Diffusion models have demonstrated impressive performance in text-to-image generation.
They utilize a text encoder and cross-attention blocks to infuse textual information into …
They utilize a text encoder and cross-attention blocks to infuse textual information into …
Anomaly detection in networks via score-based generative models
Node outlier detection in attributed graphs is a challenging problem for which there is no
method that would work well across different datasets. Motivated by the state-of-the-art …
method that would work well across different datasets. Motivated by the state-of-the-art …
In-or out-of-distribution detection via dual divergence estimation
Detecting out-of-distribution (OOD) samples is a problem of practical importance for a
reliable use of deep neural networks (DNNs) in production settings. The corollary to this …
reliable use of deep neural networks (DNNs) in production settings. The corollary to this …
Landmark-guided Diffusion Model for High-fidelity and Temporally Coherent Talking Head Generation
Audio-driven talking head generation is a significant and challenging task applicable to
various fields such as virtual avatars, film production, and online conferences. However, the …
various fields such as virtual avatars, film production, and online conferences. However, the …
Fuzzy-Conditioned Diffusion and Diffusion Projection Attention Applied to Facial Image Correction
M El Helou - 2023 IEEE International Conference on Image …, 2023 - ieeexplore.ieee.org
Image diffusion has recently shown remarkable performance in image synthesis and
implicitly as an image prior. Such a prior has been used with conditioning to solve the …
implicitly as an image prior. Such a prior has been used with conditioning to solve the …
Why SAM finetuning can benefit Out-of-Distribution Detection?
The out-of-distribution (OOD) detection task is crucial for the real-world deployment of
machine learning models. In this paper, we propose to study the problem from the …
machine learning models. In this paper, we propose to study the problem from the …