← Search

Guocheng Niu

7 accepted papers

2023

Knowledge-Constrained Answer Generation for Open-Ended Video Question Answering

AAAI 2023technical

Open-ended Video question answering (open-ended VideoQA) aims to understand video content and question semantics to generate the correct answers. Most of the best performing models define the problem as a discriminative task of multi-label classification. In real-world scenarios, however, it is diff…

Cited by 11SourcePDFScholar
2022

DU-VLG: Unifying Vision-and-Language Generation via Dual Sequence-to-Sequence Pre-training

ACL 2022findings

Due to the limitations of the model structure and pre-training objectives, existing vision-and-language generation models cannot utilize pair-wise images and text through bi-directional generation. In this paper, we propose DU-VLG, a framework which unifies vision-and-language generation as sequence…

Cited by 7SourcePDFScholar
2022

UNIMO-2: End-to-End Unified Vision-Language Grounded Learning

ACL 2022findings

Vision-Language Pre-training (VLP) has achieved impressive performance on various cross-modal downstream tasks. However, most existing methods can only learn from aligned image-caption data and rely heavily on expensive regional features, which greatly limits their scalability and performance. In th…

2021

Learning with Noisy Correspondence for Cross-modal Matching

NeurIPS 2021oral

Cross-modal matching, which aims to establish the correspondence between two different modalities, is fundamental to a variety of tasks such as cross-modal retrieval and vision-and-language understanding. Although a huge number of cross-modal matching methods have been proposed and achieved remarkab…

2021

UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

ACL 2021long

Existed pre-training methods either focus on single-modal tasks or multi-modal tasks, and cannot effectively adapt to each other. They can only utilize single-modal data (i.e., text or image) or limited multi-modal data (i.e., image-text pairs). In this work, we propose a UNIfied-MOdal pre-training…

2021

Weakly Supervised Dense Video Captioning via Jointly Usage of Knowledge Distillation and Cross-modal Matching

IJCAI 2021poster

This paper proposes an approach to Dense Video Captioning (DVC) without pairwise event-sentence annotation. First, we adopt the knowledge distilled from relevant and well solved tasks to generate high-quality event proposals. Then we incorporate contrastive loss and cycle-consistency loss typically…

2018

A New Method of Region Embedding for Text Classification

ICLR 2018poster

To represent a text as a bag of properly identified “phrases” and use the representation for processing the text is proved to be useful. The key question here is how to identify the phrases and represent them. The traditional method of utilizing n-grams can be regarded as an approximation of the app…