activity
20192023
most citedTowards artificial general intelligence via a multimodal foundation model

285 citations · 473 across the 10 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2023★ 9 cited

VDT: General-purpose Video Diffusion Transformers via Mask Modeling

Haoyu Lu, Guoxing Yang, Nanyi Fei +4

This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized…

cs.CV2023★ 21 cited

UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling

Haoyu Lu, Yuqi Huo, Guoxing Yang +4

Large-scale vision-language pre-trained models have shown promising transferability to various downstream tasks. As the size of these foundation models and the number of downstream…

cs.CV2022★ 5 cited

LGDN: Language-Guided Denoising Network for Video-Language Modeling

Haoyu Lu, Mingyu Ding, Nanyi Fei +2

Video-language modeling has attracted much attention with the rapid growth of web videos. Most existing methods assume that the video frames and text description are semantically c…

cs.CV2022★ 2 cited

COTS: Collaborative Two-Stream Vision-Language Pre-Training Model for Cross-Modal Retrieval

Haoyu Lu, Nanyi Fei, Yuqi Huo +3

Large-scale single-stream pre-training has shown dramatic performance in image-text retrieval. Regrettably, it faces low inference efficiency due to heavy attention layers. Recentl…

cs.CV2021★ 8 cited

Learning Versatile Neural Architectures by Propagating Network Codes

Mingyu Ding, Yuqi Huo, Haoyu Lu +5

This work explores how to design a single neural network capable of adapting to multiple heterogeneous vision tasks, such as image segmentation, 3D detection, and video recognition…

cs.CV2021★ 84 cited

WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training

Yuqi Huo, Manli Zhang, Guangzhen Liu +32

Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…

cs.CV2019★ 30 cited

Learning Depth-Guided Convolutions for Monocular 3D Object Detection

Mingyu Ding, Yuqi Huo, Hongwei Yi +4

3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this task…

cs.CV2019★ 14 cited

Mobile Video Action Recognition

Yuqi Huo, Xiaoli Xu, Yao Lu +3

Video action recognition, which is topical in computer vision and video analysis, aims to allocate a short video clip to a pre-defined category such as brushing hair or climbing st…