34 citations · 69 across the 18 of their papers we have counts for
9 papers · 1 filter
Towards Lossless Ultimate Vision Token Compression for VLMs
Dehua Zheng, Mouxiao Huang, Borui Jiang +2
Visual language models encounter challenges in computational efficiency and latency, primarily due to the substantial redundancy in the token representations of high-resolution ima…
PPE: Positional Preservation Embedding for Token Compression in Multimodal Large Language Models
Mouxiao Huang, Borui Jiang, Dehua Zheng +3
Multimodal large language models (MLLMs) have achieved strong performance on vision-language tasks, yet often suffer from inefficiencies due to redundant visual tokens. Existing to…
Single Domain Generalization for Few-Shot Counting via Universal Representation Matching
Xianing Chen, Si Huo, Borui Jiang +2
Few-shot counting estimates the number of target objects in an image using only a few annotated exemplars. However, domain shift severely hinders existing methods to generalize to…
GenVidBench: A 6-Million Benchmark for AI-Generated Video Detection
Zhenliang Ni, Qiangyu Yan, Mouxiao Huang +5
The rapid advancement of video generation models has made it increasingly challenging to distinguish AI-generated videos from real ones. This issue underscores the urgent need for…
Omni-Dimensional Frequency Learner for General Time Series Analysis
Xianing Chen, Hanting Chen, Hailin Hu
Frequency domain representation of time series feature offers a concise representation for handling real-world time series data with inherent complexity and dynamic nature. However…
GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization
Yirui Chen, Xudong Huang, Quan Zhang +9
The extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia…
GenDet: Towards Good Generalizations for AI-Generated Image Detection
Mingjian Zhu, Hanting Chen, Mouxiao Huang +4
The misuse of AI imagery can have harmful societal effects, prompting the creation of detectors to combat issues like the spread of fake news. Existing methods can effectively dete…
Less is More: Focus Attention for Efficient DETR
Dehua Zheng, Wenhui Dong, Hailin Hu +2
DETR-like models have significantly boosted the performance of detectors and even outperformed classical convolutional models. However, all tokens are treated equally without discr…
GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image
Mingjian Zhu, Hanting Chen, Qiangyu Yan +7
The extraordinary ability of generative models to generate photographic images has intensified concerns about the spread of disinformation, thereby leading to the demand for detect…