From the 2 of 30 linked papers with an AI index.
1 citations · 1 across the 13 of their papers we have counts for
6 papers · 1 filter
Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model
Kun Fang, Zuopeng Yang, Haibo Hu +3
The paper introduces DDR, a method that evaluates the difference between an input image and its diffusion‑model reconstruction using the classifier’s deep feature and logit represe…
Stochastic Optimal Control Sampling for Diffusion Inverse Problems
Jie Zhang, Youmei Qiu, Hanling Tian +3
Benefiting from the strong ability to capture data distributions, diffusion models have become powerful tools for solving image inverse problems. The key is to controllably steer t…
T2I-ConBench: Text-to-Image Benchmark for Continual Post-training
Zhehao Huang, Yuhang Liu, Yixin Lou +7
Continual post-training adapts a single text-to-image diffusion model to learn new tasks without incurring the cost of separate models, but naive post-training causes forgetting of…
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu, Ruiji Yu, Xinwen Cheng +2
In the open world, detecting out-of-distribution (OOD) data, whose labels are disjoint with those of in-distribution (ID) samples, is important for reliable deep neural networks (D…
Low-Dimensional Gradient Helps Out-of-Distribution Detection
Yingwen Wu, Tao Li, Xinwen Cheng +2
Detecting out-of-distribution (OOD) samples is essential for ensuring the reliability of deep neural networks (DNNs) in real-world scenarios. While previous research has predominan…
OrthCaps: An Orthogonal CapsNet with Sparse Attention Routing and Pruning
Xinyu Geng, Jiaming Wang, Jiawei Gong +4
Redundancy is a persistent challenge in Capsule Networks (CapsNet),leading to high computational costs and parameter counts. Although previous works have introduced pruning after t…