activity
20192024
most citedEgocentric Video-Language Pretraining

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

collaborators

28 papers

cs.CV2024★ 1 cited

ShowUI: One Vision-Language-Action Model for GUI Visual Agent

Kevin Qinghong Lin, Linjie Li, Difei Gao +6

Building Graphical User Interface (GUI) assistants holds significant promise for enhancing human workflow productivity. While most agents are language-based, relying on closed-sour…

cs.CV2024

Learning Video Context as Interleaved Multimodal Sequences

Kevin Qinghong Lin, Pengchuan Zhang, Difei Gao +6

Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify wh…

cs.CV2024

GUI Action Narrator: Where and When Did That Action Take Place?

Qinchen Wu, Difei Gao, Kevin Qinghong Lin +6

The advent of Multimodal LLMs has significantly enhanced image OCR recognition capabilities, making GUI automation a viable reality for increasing efficiency in digital tasks. One…

cs.CV2024★ 3 cited

VideoLLM-online: Online Video Large Language Model for Streaming Video

Joya Chen, Zhaoyang Lv, Shiwei Wu +7

Recent Large Language Models have been enhanced with vision capabilities, enabling them to comprehend images, videos, and interleaved vision-language content. However, the learning…

cs.CV2024

VideoGUI: A Benchmark for GUI Automation from Instructional Videos

Kevin Qinghong Lin, Linjie Li, Difei Gao +5

Graphical User Interface (GUI) automation holds significant promise for enhancing human productivity by assisting with computer tasks. Existing task formulations primarily focus on…

cs.CV2024

LOVA3: Learning to Visual Question Answering, Asking and Assessment

Henry Hengyuan Zhao, Pan Zhou, Difei Gao +2

Question answering, asking, and assessment are three innate human traits crucial for understanding the world and acquiring knowledge. By enhancing these capabilities, humans can mo…

cs.CV2024★ 1 cited

Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces

Juan Hu, Xin Liao, Difei Gao +4

Deepfake videos are becoming increasingly realistic, showing few tampering traces on facial areasthat vary between frames. Consequently, existing Deepfake detection methods struggl…

cs.CV2024

ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation

Difei Gao, Lei Ji, Zechen Bai +10

Graphical User Interface (GUI) automation holds significant promise for assisting users with complex tasks, thereby boosting human productivity. Existing works leveraging Large Lan…

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…

cs.CV2022★ 5 cited

MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video Question Answering

Difei Gao, Luowei Zhou, Lei Ji +3

To build Video Question Answering (VideoQA) systems capable of assisting humans in daily activities, seeking answers from long-form videos with diverse and complex events is a must…

cs.CV2022★ 1 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.CV2022

CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding

Zhijian Hou, Wanjun Zhong, Lei Ji +6

This paper tackles an emerging and challenging problem of long video temporal grounding~(VTG) that localizes video moments related to a natural language (NL) query. Compared with s…

cs.CV2022★ 4 cited

Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task

Stan Weixian Lei, Difei Gao, Jay Zhangjie Wu +4

VQA is an ambitious task aiming to answer any image-related question. However, in reality, it is hard to build such a system once for all since the needs of users are continuously…

cs.CV2022

Egocentric Video-Language Pretraining @ Ego4D Challenge 2022

Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13

In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Q…

cs.CV2022★ 45 cited

Egocentric Video-Language Pretraining

Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13

Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention…

cs.CV2022

GEB+: A Benchmark for Generic Event Boundary Captioning, Grounding and Retrieval

Yuxuan Wang, Difei Gao, Licheng Yu +3

Cognitive science has shown that humans perceive videos in terms of events separated by the state changes of dominant subjects. State changes trigger new events and are one of the…