activity
20212023
most citedMasked Image Modeling with Denoising Contrast

8 citations · 16 across the 9 of their papers we have counts for

collaborators

9 papers

cs.IR2023★ 1 cited

TagGPT: Large Language Models are Zero-shot Multimodal Taggers

Chen Li, Yixiao Ge, Jiayong Mao +2

Tags are pivotal in facilitating the effective distribution of multimedia content in various applications in the contemporary Internet era, such as search engines and recommendatio…

cs.CV2023★ 1 cited

RILS: Masked Visual Reconstruction in Language Semantic Space

Shusheng Yang, Yixiao Ge, Kun Yi +4

Both masked image modeling (MIM) and natural language supervision have facilitated the progress of transferable visual pre-training. In this work, we seek the synergy between two p…

cs.CV2022★ 8 cited

Masked Image Modeling with Denoising Contrast

Kun Yi, Yixiao Ge, Xiaotong Li +5

Since the development of self-supervised visual representation learning from contrastive learning to masked image modeling (MIM), there is no significant difference in essence, tha…

cs.CV2022★ 1 cited

Controllable Augmentations for Video Representation Learning

Rui Qian, Weiyao Lin, John See +1

This paper focuses on self-supervised video representation learning. Most existing approaches follow the contrastive learning pipeline to construct positive and negative pairs by s…

cs.CV2022★ 1 cited

Bridging Video-text Retrieval with Multiple Choice Questions

Yuying Ge, Yixiao Ge, Xihui Liu +4

Pre-training a model to learn transferable video-text representation for retrieval has attracted a lot of attention in recent years. Previous dominant works mainly adopt two separa…

cs.CV2021

CA-SSL: Class-Agnostic Semi-Supervised Learning for Detection and Segmentation

Lu Qi, Jason Kuen, Zhe Lin +7

To improve instance-level detection/segmentation performance, existing self-supervised and semi-supervised methods extract either task-unrelated or task-specific training signals f…

cs.CV2021★ 4 cited

CLIP4Caption ++: Multi-CLIP for Video Caption

Mingkang Tang, Zhanyu Wang, Zhaoyang Zeng +2

This report describes our solution to the VALUE Challenge 2021 in the captioning task. Our solution, named CLIP4Caption++, is built on X-Linear/X-Transformer, which is an advanced…

cs.CV2021

CLIP4Caption: CLIP for Video Caption

Mingkang Tang, Zhanyu Wang, Zhenhua Liu +3

Video captioning is a challenging task since it requires generating sentences describing various diverse and complex videos. Existing video captioning models lack adequate visual r…

cs.CV2021

Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization

Rui Qian, Yuxi Li, Huabin Liu +5

The crux of self-supervised video representation learning is to build general features from unlabeled videos. However, most recent works have mainly focused on high-level semantics…