activity
20182022
most citedSEED: Self-supervised Distillation For Visual Representation

74 citations · 268 across the 19 of their papers we have counts for

collaborators

27 papers

cs.CV202212 cited

Exploring Discrete Diffusion Models for Image Captioning

Zixin Zhu, Yixuan Wei, Jianfeng Wang +7

The image captioning task is typically realized by an auto-regressive method that decodes the text tokens one by one. We present a diffusion-based captioning model, dubbed the name…

cs.CV202230 cited

GRiT: A Generative Region-to-text Transformer for Object Understanding

Jialian Wu, Jianfeng Wang, Zhengyuan Yang +4

This paper presents a Generative RegIon-to-Text transformer, GRiT, for object understanding. The spirit of GRiT is to formulate object understanding as <region, text> pairs, where…

cs.CV2022

ReCo: Region-Controlled Text-to-Image Generation

Zhengyuan Yang, Jianfeng Wang, Zhe Gan +8

Recently, large-scale text-to-image (T2I) models have shown impressive performance in generating high-fidelity images, but with limited controllability, e.g., precisely specifying…

cs.CV20222 cited

Non-Contrastive Learning Meets Language-Image Pre-Training

Jinghao Zhou, Li Dong, Zhe Gan +2

Contrastive language-image pre-training (CLIP) serves as a de-facto standard to align images and texts. Nonetheless, the loose correlation between images and texts of web-crawled d…

cs.CV202213 cited

Vision-Language Pre-training: Basics, Recent Advances, and Future Trends

Zhe Gan, Linjie Li, Chunyuan Li +3

This paper surveys vision-language pre-training (VLP) methods for multimodal intelligence that have been developed in the last few years. We group these approaches into three categ…

cs.CV2022

Cross-modal Representation Learning for Zero-shot Action Recognition

Chung-Ching Lin, Kevin Lin, Linjie Li +2

We present a cross-modal Transformer-based framework, which jointly encodes video data and text labels for zero-shot action recognition (ZSAR). Our model employs a conceptually new…