activity
20182023
most citedXGPT: Cross-modal Generative Pre-Training for Image Captioning

20 citations · 27 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023

AssistGPT: A General Multi-modal Assistant that can Plan, Execute, Inspect, and Learn

Difei Gao, Lei Ji, Luowei Zhou +4

Recent research on Large Language Models (LLMs) has led to remarkable advancements in general NLP AI assistants. Some studies have further explored the use of LLMs for planning and…

cs.CV2023

GroundNLQ @ Ego4D Natural Language Queries Challenge 2023

Zhijian Hou, Lei Ji, Difei Gao +7

In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocent…

cs.CV20221 cited

An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022

Zhijian Hou, Wanjun Zhong, Lei Ji +6

This technical report describes the CONE approach for Ego4D Natural Language Queries (NLQ) Challenge in ECCV 2022. We leverage our model CONE, an efficient window-centric COarse-to…

cs.CV20212 cited

Hybrid Reasoning Network for Video-based Commonsense Captioning

Weijiang Yu, Jian Liang, Lei Ji +4

The task of video-based commonsense captioning aims to generate event-wise captions and meanwhile provide multiple commonsense descriptions (e.g., attribute, effect and intention)…

cs.CV2021

CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval

Huaishao Luo, Lei Ji, Ming Zhong +4

Video-text retrieval plays an essential role in multi-modal research and has been widely used in many real-world web applications. The CLIP (Contrastive Language-Image Pre-training…

cs.CV2021

GODIVA: Generating Open-DomaIn Videos from nAtural Descriptions

Chenfei Wu, Lun Huang, Qianxi Zhang +5

Generating videos from text is a challenging task due to its high computational requirements for training and infinite possible answers for evaluation. Existing works typically exp…