activity
20202026
most citedMultimodal Federated Learning via Contrastive Representation Ensemble

36 citations · 49 across the 18 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models

Yimu Wang, Weiming Zhuang, Chen Chen +3

In the era of deep learning, the increasing number of pre-trained models available online presents a wealth of knowledge. These models, developed with diverse architectures and tra…

cs.CV2025

HAWAII: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models

Yimu Wang, Mozhgan Nasr Azadani, Sean Sedwards +1

Improving the visual understanding ability of vision-language models (VLMs) is crucial for enhancing their performance across various tasks. While using multiple pretrained visual…

cs.CV2025

Survey of Video Diffusion Models: Foundations, Implementations, and Applications

Yimu Wang, Xuye Liu, Wei Pang +4

Recent advances in diffusion models have revolutionized video generation, offering superior temporal consistency and visual quality compared to traditional generative adversarial n…

cs.CV2025

LEO-MINI: An Efficient Multimodal Large Language Model using Conditional Token Reduction and Mixture of Multi-Modal Experts

Yimu Wang, Mozhgan Nasr Azadani, Sean Sedwards +1

Redundancy of visual tokens in multi-modal large language models (MLLMs) significantly reduces their computational efficiency. Recent approaches, such as resamplers and summarizers…

cs.CV2025

OV-SCAN: Semantically Consistent Alignment for Novel Object Discovery in Open-Vocabulary 3D Object Detection

Adrian Chow, Evelien Riddell, Yimu Wang +2

Open-vocabulary 3D object detection for autonomous driving aims to detect novel objects beyond the predefined training label sets in point cloud scenes. Existing approaches achieve…

cs.CV2025

Mitigating the Modality Gap: Few-Shot Out-of-Distribution Detection with Multi-modal Prototypes and Image Bias Estimation

Yimu Wang, Evelien Riddell, Adrian Chow +2

Existing vision-language model (VLM)-based methods for out-of-distribution (OOD) detection typically rely on similarity scores between input images and in-distribution (ID) text pr…