9 citations · 15 across the 7 of their papers we have counts for
7 papers
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…
ControlMTR: Control-Guided Motion Transformer with Scene-Compliant Intention Points for Feasible Motion Prediction
Jiawei Sun, Chengran Yuan, Shuo Sun +7
The ability to accurately predict feasible multimodal future trajectories of surrounding traffic participants is crucial for behavior planning in autonomous vehicles. The Motion Tr…
Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
Shuailei Ma, Chen-Wei Xie, Ying Wei +5
Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such as CLIP, for various downstream tasks. However, there is no work that provides a c…
SKDF: A Simple Knowledge Distillation Framework for Distilling Open-Vocabulary Knowledge to Open-world Object Detector
Shuailei Ma, Yuefeng Wang, Ying Wei +4
In this paper, we attempt to specialize the VLM model for OWOD tasks by distilling its open-world knowledge into a language-agnostic detector. Surprisingly, we observe that the com…
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…
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…
CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection
Shuailei Ma, Yuefeng Wang, Jiaqi Fan +4
Open-world object detection (OWOD), as a more general and challenging goal, requires the model trained from data on known objects to detect both known and unknown objects and incre…