829 citations · 4.3k across the 90 of their papers we have counts for
90 papers
CLE Diffusion: Controllable Light Enhancement Diffusion Model
Yuyang Yin, Dejia Xu, Chuangchuang Tan +3
Low light enhancement has gained increasing importance with the rapid development of visual creation and editing. However, most existing enhancement algorithms are designed to homo…
CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation
Hongguang Zhu, Yunchao Wei, Xiaodan Liang +2
Vision-Language Pretraining (VLP) has shown impressive results on diverse downstream tasks by offline training on large-scale datasets. Regarding the growing nature of real-world d…
StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data
Yanda Li, Chi Zhang, Gang Yu +6
The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary res…
Disentangled Pre-training for Image Matting
Yanda Li, Zilong Huang, Gang Yu +3
Image matting requires high-quality pixel-level human annotations to support the training of a deep model in recent literature. Whereas such annotation is costly and hard to scale,…
Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learning
Man Liu, Feng Li, Chunjie Zhang +3
Generalized Zero-Shot Learning (GZSL) identifies unseen categories by knowledge transferred from the seen domain, relying on the intrinsic interactions between visual and semantic…
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
Kunyang Han, Yong Liu, Jun Hao Liew +8
Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred…