29 citations · 110 across the 8 of their papers we have counts for
8 papers
ArtGPT-4: Towards Artistic-understanding Large Vision-Language Models with Enhanced Adapter
Zhengqing Yuan, Yunhong He, Kun Wang +2
The success of large language models (LLMs) has inspired an emerging research field of multimodal learning. However, a grand challenge of exploiting LLMs for multimodal learning is…
Explore the Power of Synthetic Data on Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. The few training samples restrict the performance o…
An Effective Crop-Paste Pipeline for Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. However, detecting novel categories with only a few…
INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li +24
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However,…
Adapting Object Detectors with Conditional Domain Normalization
Peng Su, Kun Wang, Xingyu Zeng +4
Real-world object detectors are often challenged by the domain gaps between different datasets. In this work, we present the Conditional Domain Normalization (CDN) to bridge the do…
Scene Graph Generation from Objects, Phrases and Region Captions
Yikang Li, Wanli Ouyang, Bolei Zhou +2
Object detection, scene graph generation and region captioning, which are three scene understanding tasks at different semantic levels, are tied together: scene graphs are generate…