most citedFGAHOI: Fine-Grained Anchors for Human-Object Interaction Detection

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual Preferences

Hongyan Zhi, Peihao Chen, Junyan Li +6

Research on 3D Vision-Language Models (3D-VLMs) is gaining increasing attention, which is crucial for developing embodied AI within 3D scenes, such as visual navigation and embodie…

cs.CV2024

LoTLIP: Improving Language-Image Pre-training for Long Text Understanding

Wei Wu, Kecheng Zheng, Shuailei Ma +7

Understanding long text is of great demands in practice but beyond the reach of most language-image pre-training (LIP) models. In this work, we empirically confirm that the key rea…

cs.CV2024

DreamLIP: Language-Image Pre-training with Long Captions

Kecheng Zheng, Yifei Zhang, Wei Wu +5

Language-image pre-training largely relies on how precisely and thoroughly a text describes its paired image. In practice, however, the contents of an image can be so rich that wel…

cs.CV20231 cited

Detecting the open-world objects with the help of the Brain

Shuailei Ma, Yuefeng Wang, Ying Wei +5

Open World Object Detection (OWOD) is a novel computer vision task with a considerable challenge, bridging the gap between classic object detection (OD) benchmarks and real-world o…

cs.CV20232 cited

FGAHOI: Fine-Grained Anchors for Human-Object Interaction Detection

Shuailei Ma, Yuefeng Wang, Shanze Wang +1

Human-Object Interaction (HOI), as an important problem in computer vision, requires locating the human-object pair and identifying the interactive relationships between them. The…