25 citations · 61 across the 14 of their papers we have counts for
13 papers · 1 filter
CCM: Adding Conditional Controls to Text-to-Image Consistency Models
Jie Xiao, Kai Zhu, Han Zhang +5
Consistency Models (CMs) have showed a promise in creating visual content efficiently and with high quality. However, the way to add new conditional controls to the pretrained CMs…
Background Activation Suppression for Weakly Supervised Object Localization and Semantic Segmentation
Wei Zhai, Pingyu Wu, Kai Zhu +3
Weakly supervised object localization and semantic segmentation aim to localize objects using only image-level labels. Recently, a new paradigm has emerged by generating a foregrou…
Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-trained Vision-Language Models
Kecheng Zheng, Wei Wu, Ruili Feng +6
Prompt tuning and adapter tuning have shown great potential in transferring pre-trained vision-language models (VLMs) to various downstream tasks. In this work, we design a new typ…
Cones 2: Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu, Yifei Zhang, Yujun Shen +7
Synthesizing images with user-specified subjects has received growing attention due to its practical applications. Despite the recent success in single subject customization, exist…
Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection
Fan Lu, Kai Zhu, Wei Zhai +2
Semantically coherent out-of-distribution (SCOOD) detection aims to discern outliers from the intended data distribution with access to unlabeled extra set. The coexistence of in-d…
Cones: Concept Neurons in Diffusion Models for Customized Generation
Zhiheng Liu, Ruili Feng, Kai Zhu +6
Human brains respond to semantic features of presented stimuli with different neurons. It is then curious whether modern deep neural networks admit a similar behavior pattern. Spec…
FAMLP: A Frequency-Aware MLP-Like Architecture For Domain Generalization
Kecheng Zheng, Yang Cao, Kai Zhu +2
MLP-like models built entirely upon multi-layer perceptrons have recently been revisited, exhibiting the comparable performance with transformers. It is one of most promising archi…
Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning
Kai Zhu, Wei Zhai, Yang Cao +2
Non-exemplar class-incremental learning is to recognize both the old and new classes when old class samples cannot be saved. It is a challenging task since representation optimizat…
Self-Paced Imbalance Rectification for Class Incremental Learning
Zhiheng Liu, Kai Zhu, Yang Cao
Exemplar-based class-incremental learning is to recognize new classes while not forgetting old ones, whose samples can only be saved in limited memory. The ratio fluctuation of new…
Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior
Feng Zhang, Yuanjie Shao, Yishi Sun +3
Deep learning-based methods for low-light image enhancement typically require enormous paired training data, which are impractical to capture in real-world scenarios. Recently, uns…
Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning
Kai Zhu, Yang Cao, Wei Zhai +2
Few-shot class-incremental learning is to recognize the new classes given few samples and not forget the old classes. It is a challenging task since representation optimization and…
Self-Supervised Tuning for Few-Shot Segmentation
Kai Zhu, Wei Zhai, Zheng-Jun Zha +1
Few-shot segmentation aims at assigning a category label to each image pixel with few annotated samples. It is a challenging task since the dense prediction can only be achieved un…
One-Shot Texture Retrieval with Global Context Metric
Kai Zhu, Wei Zhai, Zheng-Jun Zha +1
In this paper, we tackle one-shot texture retrieval: given an example of a new reference texture, detect and segment all the pixels of the same texture category within an arbitrary…