32 citations · 35 across the 5 of their papers we have counts for
5 papers
UNIMO-2: End-to-End Unified Vision-Language Grounded Learning
Wei Li, Can Gao, Guocheng Niu +5
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-cap…
DU-VLG: Unifying Vision-and-Language Generation via Dual Sequence-to-Sequence Pre-training
Luyang Huang, Guocheng Niu, Jiachen Liu +2
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-direct…
Weakly Supervised Dense Video Captioning via Jointly Usage of Knowledge Distillation and Cross-modal Matching
Bofeng Wu, Guocheng Niu, Jun Yu +3
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 ta…
UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning
Wei Li, Can Gao, Guocheng Niu +5
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…
Parse Concurrent Data Structures: BST as an Example
Keren Zhou, Guocheng Niu, Wuzhao Zhang +2
Designing concurrent data structures should follow some basic rules. By separating the algorithms into two phases, we present guidelines for scalable data structures, with a analys…