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20232026
most citedUMIT: Unifying Medical Imaging Tasks via Vision-Language Models

1 citations · 3 across the 12 of their papers we have counts for

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cs.CV2026

Anchor and Adapt: Asymmetric Prompt Adaptation for Few-Shot Industrial Anomaly Detection

Mengyang Zhao, Teng Fu, Haiyang Yu +3

In few-shot industrial anomaly detection, the few normal target images provide no direct defect supervision, making anomaly prompts difficult to learn from these samples alone. Som…

cs.CV2026

IterCAD: Iterative Program Repair for CAD Code Generation from Orthographic Views

Yuchuan Wu, Ke Niu, Haiyang Yu +3

Generating executable parametric CAD code from dimension-annotated orthographic drawings is a challenging task requiring geometric understanding, procedural reasoning, and precise…

cs.CV2026

AMR-CCR: Anchored Modular Retrieval for Continual Chinese Character Recognition

Yuchuan Wu, Yinglian Zhu, Haiyang Yu +3

Ancient Chinese character recognition is a core capability for cultural heritage digitization, yet real-world workflows are inherently non-stationary: newly excavated materials are…

cs.CV2025

CME-CAD: Heterogeneous Collaborative Multi-Expert Reinforcement Learning for CAD Code Generation

Ke Niu, Haiyang Yu, Zhuofan Chen +7

Computer-Aided Design (CAD) is essential in industrial design, but the complexity of traditional CAD modeling and workflows presents significant challenges for automating the gener…

cs.CV2025

OmniPT: Unleashing the Potential of Large Vision Language Models for Pedestrian Tracking and Understanding

Teng Fu, Mengyang Zhao, Ke Niu +2

LVLMs have been shown to perform excellently in image-level tasks such as VQA and caption. However, in many instance-level tasks, such as visual grounding and object detection, LVL…

cs.CV2025

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning

Mengyang Zhao, Teng Fu, Haiyang Yu +2

Few-Shot Industrial Anomaly Detection (FS-IAD) has important applications in automating industrial quality inspection. Recently, some FS-IAD methods based on Large Vision-Language…

cs.CV2025

CReFT-CAD: Boosting Orthographic Projection Reasoning for CAD via Reinforcement Fine-Tuning

Ke Niu, Zhuofan Chen, Haiyang Yu +5

Computer-Aided Design (CAD) plays a pivotal role in industrial manufacturing. Orthographic projection reasoning underpins the entire CAD workflow, encompassing design, manufacturin…

cs.CV2025★ 1 cited

UMIT: Unifying Medical Imaging Tasks via Vision-Language Models

Haiyang Yu, Siyang Yi, Ke Niu +2

With the rapid advancement of deep learning, particularly in the field of medical image analysis, an increasing number of Vision-Language Models (VLMs) are being widely applied to…

cs.CV2025

PHT-CAD: Efficient CAD Parametric Primitive Analysis with Progressive Hierarchical Tuning

Ke Niu, Yuwen Chen, Haiyang Yu +4

Computer-Aided Design (CAD) plays a pivotal role in industrial manufacturing, yet 2D Parametric Primitive Analysis (PPA) remains underexplored due to two key challenges: structural…

cs.CV2025★ 1 cited

EVE: Towards End-to-End Video Subtitle Extraction with Vision-Language Models

Haiyang Yu, Mengyang Zhao, Jinghui Lu +8

Video subtitles play a crucial role in short videos and movies, as they not only help models better understand video content but also support applications such as video translation…

cs.CV2025

ChatReID: Open-ended Interactive Person Retrieval via Hierarchical Progressive Tuning for Vision Language Models

Ke Niu, Haiyang Yu, Mengyang Zhao +6

Person re-identification (Re-ID) is a crucial task in computer vision, aiming to recognize individuals across non-overlapping camera views. While recent advanced vision-language mo…

cs.CV2024★ 1 cited

Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-Training

Ke Niu, Haiyang Yu, Xuelin Qian +3

Existing person re-identification (Re-ID) methods principally deploy the ImageNet-1K dataset for model initialization, which inevitably results in sub-optimal situations due to the…

cs.CV2023

DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions

Teng Fu, Xiaocong Wang, Haiyang Yu +3

Multiple object tracking (MOT) tends to become more challenging when severe occlusions occur. In this paper, we analyze the limitations of traditional Convolutional Neural Network-…