2 citations · 4 across the 8 of their papers we have counts for
8 papers
VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer
Rui Lin, Chuanming Wang, Huadong Ma
With the rapid development of pre-training technologies, adapting large-scale Vision-Language Models (VLMs) for video understanding \emph{\ie} image-to-video transfer learning has…
XR-VLM: Cross-Relationship Modeling with Multi-part Prompts and Visual Features for Fine-Grained Recognition
Chuanming Wang, Henming Mao, Huanhuan Zhang +2
Vision-Language Models (VLMs) have demonstrated impressive performance on various visual tasks, yet they still require adaptation on downstream tasks to achieve optimal performance…
Region-Aware Exposure Consistency Network for Mixed Exposure Correction
Jin Liu, Huiyuan Fu, Chuanming Wang +1
Exposure correction aims to enhance images suffering from improper exposure to achieve satisfactory visual effects. Despite recent progress, existing methods generally mitigate eit…
Learning Exposure Correction in Dynamic Scenes
Jin Liu, Bo Wang, Chuanming Wang +2
Exposure correction aims to enhance visual data suffering from improper exposures, which can greatly improve satisfactory visual effects. However, previous methods mainly focus on…
Mutual Distillation Learning For Person Re-Identification
Huiyuan Fu, Kuilong Cui, Chuanming Wang +2
With the rapid advancements in deep learning technologies, person re-identification (ReID) has witnessed remarkable performance improvements. However, the majority of prior works h…
Towards Efficient Object Re-Identification with A Novel Cloud-Edge Collaborative Framework
Chuanming Wang, Yuxin Yang, Mengshi Qi +1
Object re-identification (ReID) is committed to searching for objects of the same identity across cameras, and its real-world deployment is gradually increasing. Current ReID metho…
Weakly-Supervised Temporal Action Localization by Inferring Salient Snippet-Feature
Wulian Yun, Mengshi Qi, Chuanming Wang +1
Weakly-supervised temporal action localization aims to locate action regions and identify action categories in untrimmed videos simultaneously by taking only video-level labels as…
Coarse-to-Fine Video Denoising with Dual-Stage Spatial-Channel Transformer
Wulian Yun, Mengshi Qi, Chuanming Wang +2
Video denoising aims to recover high-quality frames from the noisy video. While most existing approaches adopt convolutional neural networks~(CNNs) to separate the noise from the o…