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hellonote's Introduction

Hi there 👋

I'm Tianheng Cheng, pursuing my Ph.D. now and working on Vision.

Previous works/publications are listed at Google Scholar 📚.

Currently, I'm devoted in the research on visual-language modeling and multimodal models. Before that, I mainly focused on fundamental tasks such as object detection and instance segmentation, as well as visual perception for autonomous driving.

Highlighted Works:

  • The latest works 🔥: YOLO-World (CVPR 2024) for real-time open-vocabulary object detection; Symphonies (CVPR 2024) for camera-based 3D scene completion.
  • SparseInst (CVPR 2022) aims for real-time instance segmentation with a simple fully convolutional framework! MobileInst (AAAI 2024) further explores temporal consistency and kernel reuse for efficient mobile video instance segmentation.
  • BoxTeacher (CVPR 2023) bridges the gap between fully supervised and box-supervised instance segmentation. With ~1/10 annotation cost, BoxTeacher can achieve 93% performance versus fully supervised methods.
  • BMask R-CNN (ECCV 2020) is the first work to introduce boundary modeling for objects and aims for high-performance instance segmentation. It leads the research about object boundaries for instance segmentation.
  • GKT (arXiv) addresses the ill-posed 2D-to-3D (Surrounding views to Bird-Eye views) transformation with the concern about accuracy and speed, especially for practical implementation for autonomous systems.

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