activity
20222024
most citedExploring Dynamic Transformer for Efficient Object Tracking

17 citations · 34 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2024

GLDesigner: Leveraging Multi-Modal LLMs as Designer for Enhanced Aesthetic Text Glyph Layouts

Junwen He, Yifan Wang, Lijun Wang +7

Text logo design heavily relies on the creativity and expertise of professional designers, in which arranging element layouts is one of the most important procedures. However, this…

cs.AI2024

MetaDesigner: Advancing Artistic Typography Through AI-Driven, User-Centric, and Multilingual WordArt Synthesis

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li +11

MetaDesigner introduces a transformative framework for artistic typography synthesis, powered by Large Language Models (LLMs) and grounded in a user-centric design paradigm. Its fo…

cs.CV2024★ 17 cited

Exploring Dynamic Transformer for Efficient Object Tracking

Jiawen Zhu, Xin Chen, Haiwen Diao +6

The speed-precision trade-off is a critical problem for visual object tracking which usually requires low latency and deployment on constrained resources. Existing solutions for ef…

cs.CV2024

DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception

Xiang Huang, Zhi-Qi Cheng, Jun-Yan He +3

The advancement of autonomous driving systems hinges on the ability to achieve low-latency and high-accuracy perception. To address this critical need, this paper introduces Dynami…

cs.CV2024★ 1 cited

WordArt Designer API: User-Driven Artistic Typography Synthesis with Large Language Models on ModelScope

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li +10

This paper introduces the WordArt Designer API, a novel framework for user-driven artistic typography synthesis utilizing Large Language Models (LLMs) on ModelScope. We address the…

cs.CV2023

Tracking with Human-Intent Reasoning

Jiawen Zhu, Zhi-Qi Cheng, Jun-Yan He +5

Advances in perception modeling have significantly improved the performance of object tracking. However, the current methods for specifying the target object in the initial frame a…

cs.CL2023

WordArt Designer: User-Driven Artistic Typography Synthesis using Large Language Models

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li +10

This paper introduces WordArt Designer, a user-driven framework for artistic typography synthesis, relying on the Large Language Model (LLM). The system incorporates four key modul…

cs.CV2023★ 5 cited

Tracking Anything in High Quality

Jiawen Zhu, Zhenyu Chen, Zeqi Hao +9

Visual object tracking is a fundamental video task in computer vision. Recently, the notably increasing power of perception algorithms allows the unification of single/multiobject…

eess.IV2023★ 1 cited

Thoracic Cartilage Ultrasound-CT Registration using Dense Skeleton Graph

Zhongliang Jiang, Chenyang Li, Xuesong Li +1

Autonomous ultrasound (US) imaging has gained increased interest recently, and it has been seen as a potential solution to overcome the limitations of free-hand US examinations, su…

cs.CV2023★ 1 cited

KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration

Xu Bao, Zhi-Qi Cheng, Jun-Yan He +8

Accurate facial landmark detection is critical for facial analysis tasks, yet prevailing heatmap and coordinate regression methods grapple with prohibitive computational costs and…

cs.CV2023★ 1 cited

DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li +5

Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that has yet to be thoroughly explored in existing research. To address this gap, we presen…

cs.CV2022★ 2 cited

LongShortNet: Exploring Temporal and Semantic Features Fusion in Streaming Perception

Chenyang Li, Zhi-Qi Cheng, Jun-Yan He +6

Streaming perception is a critical task in autonomous driving that requires balancing the latency and accuracy of the autopilot system. However, current methods for streaming perce…

cs.CV2022★ 6 cited

ProContEXT: Exploring Progressive Context Transformer for Tracking

Jin-Peng Lan, Zhi-Qi Cheng, Jun-Yan He +6

Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template. This causes tracking to inevitably fail in fast-changing and crowded scenes, as i…