1.7k citations · 1.8k across the 8 of their papers we have counts for
8 papers
Examining User-Friendly and Open-Sourced Large GPT Models: A Survey on Language, Multimodal, and Scientific GPT Models
Kaiyuan Gao, Sunan He, Zhenyu He +4
Generative pre-trained transformer (GPT) models have revolutionized the field of natural language processing (NLP) with remarkable performance in various tasks and also extend thei…
D3G: Exploring Gaussian Prior for Temporal Sentence Grounding with Glance Annotation
Hanjun Li, Xiujun Shu, Sunan He +5
Temporal sentence grounding (TSG) aims to locate a specific moment from an untrimmed video with a given natural language query. Recently, weakly supervised methods still have a lar…
Efficient Multi-Scale Attention Module with Cross-Spatial Learning
Daliang Ouyang, Su He, Guozhong Zhang +4
Remarkable effectiveness of the channel or spatial attention mechanisms for producing more discernible feature representation are illustrated in various computer vision tasks. Howe…
Vision-Language Pre-training with Object Contrastive Learning for 3D Scene Understanding
Taolin Zhang, Sunan He, Dai Tao +3
In recent years, vision language pre-training frameworks have made significant progress in natural language processing and computer vision, achieving remarkable performance improve…
VLMAE: Vision-Language Masked Autoencoder
Sunan He, Taian Guo, Tao Dai +4
Image and language modeling is of crucial importance for vision-language pre-training (VLP), which aims to learn multi-modal representations from large-scale paired image-text data…
Exploiting Feature Diversity for Make-up Temporal Video Grounding
Xiujun Shu, Wei Wen, Taian Guo +3
This technical report presents the 3rd winning solution for MTVG, a new task introduced in the 4-th Person in Context (PIC) Challenge at ACM MM 2022. MTVG aims at localizing the te…
Open-Vocabulary Multi-Label Classification via Multi-Modal Knowledge Transfer
Sunan He, Taian Guo, Tao Dai +3
Real-world recognition system often encounters the challenge of unseen labels. To identify such unseen labels, multi-label zero-shot learning (ML-ZSL) focuses on transferring knowl…
TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots
Wentao Ma, Yiming Cui, Nan Shao +5
We consider the importance of different utterances in the context for selecting the response usually depends on the current query. In this paper, we propose the model TripleNet to…