activity
20192024
most citedEgocentric Video-Language Pretraining

45 citations · 131 across the 28 of their papers we have counts for

collaborators
Showing 2023Show all

9 papers · 1 filter

cs.CV2023★ 6 cited

CVPR 2023 Text Guided Video Editing Competition

Jay Zhangjie Wu, Xiuyu Li, Difei Gao +17

Humans watch more than a billion hours of video per day. Most of this video was edited manually, which is a tedious process. However, AI-enabled video-generation and video-editing…

cs.CV2023★ 15 cited

Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation

David Junhao Zhang, Jay Zhangjie Wu, Jia-Wei Liu +5

Significant advancements have been achieved in the realm of large-scale pre-trained text-to-video Diffusion Models (VDMs). However, previous methods either rely solely on pixel-bas…

cs.CV2023

Recap: Detecting Deepfake Video with Unpredictable Tampered Traces via Recovering Faces and Mapping Recovered Faces

Juan Hu, Xin Liao, Difei Gao +4

The exploitation of Deepfake techniques for malicious intentions has driven significant research interest in Deepfake detection. Deepfake manipulations frequently introduce random…

cs.CV2023★ 6 cited

UniVTG: Towards Unified Video-Language Temporal Grounding

Kevin Qinghong Lin, Pengchuan Zhang, Joya Chen +5

Video Temporal Grounding (VTG), which aims to ground target clips from videos (such as consecutive intervals or disjoint shots) according to custom language queries (e.g., sentence…

cs.CV2023★ 19 cited

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★ 1 cited

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.MM2023

Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection

Juan Hu, Xin Liao, Difei Gao +4

Deepfake techniques have been widely used for malicious purposes, prompting extensive research interest in developing Deepfake detection methods. Deepfake manipulations typically i…

cs.CV2023★ 1 cited

Affordance Grounding from Demonstration Video to Target Image

Joya Chen, Difei Gao, Kevin Qinghong Lin +1

Humans excel at learning from expert demonstrations and solving their own problems. To equip intelligent robots and assistants, such as AR glasses, with this ability, it is essenti…

cs.CV2023★ 6 cited

Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection

Juan Hu, Xin Liao, Difei Gao +4

Deepfake techniques have been widely used for malicious purposes, prompting extensive research interest in developing Deepfake detection methods. Deepfake manipulations typically i…