most citedUniVTG: Towards Unified Video-Language Temporal Grounding

6 citations · 10 across the 5 of their papers we have counts for

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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.CV20243 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

From a Social Cognitive Perspective: Context-aware Visual Social Relationship Recognition

Shiwei Wu, Chao Zhang, Joya Chen +4

People's social relationships are often manifested through their surroundings, with certain objects or interactions acting as symbols for specific relationships, e.g., wedding ring…

cs.CV20236 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.CV20231 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…