15 citations · 36 across the 18 of their papers we have counts for
11 papers · 1 filter
Dr. Seg: Revisiting GRPO Training for Visual Large Language Models through Perception-Oriented Design
Haoxiang Sun, Tao Wang, Chenwei Tang +2
Following the success of Group Relative Policy Optimization (GRPO) in foundation LLMs, an increasing number of works have sought to adapt GRPO to Visual Large Language Models (VLLM…
Adaptive Image Zoom-in with Bounding Box Transformation for UAV Object Detection
Tao Wang, Chenyu Lin, Chenwei Tang +5
Detecting objects from UAV-captured images is challenging due to the small object size. In this work, a simple and efficient adaptive zoom-in framework is explored for object detec…
Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrieval
Yifan Wang, Tao Wang, Chenwei Tang +5
Recently, prompt learning has demonstrated remarkable success in adapting pre-trained Vision-Language Models (VLMs) to various downstream tasks such as image classification. Howeve…
SaENeRF: Suppressing Artifacts in Event-based Neural Radiance Fields
Yuanjian Wang, Yufei Deng, Rong Xiao +4
Event cameras are neuromorphic vision sensors that asynchronously capture changes in logarithmic brightness changes, offering significant advantages such as low latency, low power…
Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection
Jingyu Xing, Chenwei Tang, Tao Wang +5
Recent advances in unsupervised anomaly detection (UAD) have shifted from single-class to multi-class scenarios. In such complex contexts, the increasing pattern diversity has brou…
EBAD-Gaussian: Event-driven Bundle Adjusted Deblur Gaussian Splatting
Yufei Deng, Yuanjian Wang, Rong Xiao +6
While 3D Gaussian Splatting (3D-GS) achieves photorealistic novel view synthesis, its performance degrades with motion blur. In scenarios with rapid motion or low-light conditions,…
Zero-Shot Aerial Object Detection with Visual Description Regularization
Zhengqing Zang, Chenyu Lin, Chenwei Tang +2
Existing object detection models are mainly trained on large-scale labeled datasets. However, annotating data for novel aerial object classes is expensive since it is time-consumin…
VCL Challenges 2023 at ICCV 2023 Technical Report: Bi-level Adaptation Method for Test-time Adaptive Object Detection
Chenyu Lin, Yusheng He, Zhengqing Zang +3
This report outlines our team's participation in VCL Challenges B Continual Test_time Adaptation, focusing on the technical details of our approach. Our primary focus is Testtime A…
Attribute Localization and Revision Network for Zero-Shot Learning
Junzhe Xu, Suling Duan, Chenwei Tang +2
Zero-shot learning enables the model to recognize unseen categories with the aid of auxiliary semantic information such as attributes. Current works proposed to detect attributes f…
GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model
Caiyang Yu, Xianggen Liu, Yifan Wang +5
Neural Architecture Search (NAS) has emerged as one of the effective methods to design the optimal neural network architecture automatically. Although neural architectures have ach…
Cluster-based Contrastive Disentangling for Generalized Zero-Shot Learning
Yi Gao, Chenwei Tang, Jiancheng Lv
Generalized Zero-Shot Learning (GZSL) aims to recognize both seen and unseen classes by training only the seen classes, in which the instances of unseen classes tend to be biased t…