22 citations · 53 across the 21 of their papers we have counts for
21 papers
DARS: Dual-Level Credit Assignment RL with Structured Reasoning for Instruction-Based Image Editing
Haoxiang Cao, Jiajiong Cao, Xuanpu Zhang +2
Instruction-based image editing uses a planner-renderer pipeline: a vision-language model (VLM) first converts the instruction into an edit plan, and a diffusion model then execute…
AnyStyle: A Single LoRA is Sufficient for Image-Guided Style Transfer
Yongwen Lai, Chaoqun Wang
Image-guided style transfer aims to apply the artistic characteristics of a style image to a content image while preserving its semantic structure and layout. Despite advances in d…
Region-Constrained Group Relative Policy Optimization for Flow-Based Image Editing
Zhuohan Ouyang, Zhe Qian, Wenhuo Cui +1
Instruction-guided image editing requires balancing target modification with non-target preservation. Recently, flow-based models have emerged as a strong and increasingly adopted…
FusionEdit: Semantic Fusion and Attention Modulation for Training-Free Image Editing
Yongwen Lai, Chaoqun Wang, Shaobo Min
Text-guided image editing aims to modify specific regions according to the target prompt while preserving the identity of the source image. Recent methods exploit explicit binary m…
GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks
Wei Zhang, Chaoqun Wang, Zixuan Guan +4
Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation. Existing slice discovery approaches l…
Unlock the Power of Unlabeled Data in Language Driving Model
Chaoqun Wang, Jie Yang, Xiaobin Hong +1
Recent Vision-based Large Language Models~(VisionLLMs) for autonomous driving have seen rapid advancements. However, such promotion is extremely dependent on large-scale high-quali…
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection
Chaoqun Wang, Xiaobin Hong, Wenzhong Li +1
LiDAR-based 3D object detection presents significant challenges due to the inherent sparsity of LiDAR points. A common solution involves long-term temporal LiDAR data to densify th…
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration
Chaoqun Wang, Yiran Qin, Zijian Kang +2
Recent camera-based 3D object detection is limited by the precision of transforming from image to 3D feature spaces, as well as the accuracy of object localization within the 3D sp…
SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection
Yiran Qin, Chaoqun Wang, Zijian Kang +3
In this paper, we propose a novel training strategy called SupFusion, which provides an auxiliary feature level supervision for effective LiDAR-Camera fusion and significantly boos…
DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF
Chaowei Liu, Jichun Li, Yihua Teng +4
For capturing colored document images, e.g. posters and magazines, it is common that multiple degradations such as shadows, wrinkles, etc., are simultaneously introduced due to ext…
Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domains
Jie Yang, Chaoqun Wang, Zhen Li +2
This paper presents Scalable Semantic Transfer (SST), a novel training paradigm, to explore how to leverage the mutual benefits of the data from different label domains (i.e. vario…
Region-Enhanced Feature Learning for Scene Semantic Segmentation
Xin Kang, Chaoqun Wang, Xuejin Chen
Semantic segmentation in complex scenes relies not only on object appearance but also on object location and the surrounding environment. Nonetheless, it is difficult to model long…
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast
Kangcheng Liu, Xinhu Zheng, Chaoqun Wang +3
Contrastive learning has recently demonstrated great potential for unsupervised pre-training in 3D scene understanding tasks. However, most existing work randomly selects point fea…
Semantics-Preserving Sketch Embedding for Face Generation
Binxin Yang, Xuejin Chen, Chaoqun Wang +3
With recent advances in image-to-image translation tasks, remarkable progress has been witnessed in generating face images from sketches. However, existing methods frequently fail…
Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency
Jie Yang, Ye Zhu, Chaoqun Wang +2
Integrating multi-modal data to promote medical image analysis has recently gained great attention. This paper presents a novel scheme to learn the mutual benefits of different mod…
Dual Progressive Prototype Network for Generalized Zero-Shot Learning
Chaoqun Wang, Shaobo Min, Xuejin Chen +2
Generalized Zero-Shot Learning (GZSL) aims to recognize new categories with auxiliary semantic information,e.g., category attributes. In this paper, we handle the critical issue of…
Text-Aware Single Image Specular Highlight Removal
Shiyu Hou, Chaoqun Wang, Weize Quan +2
Removing undesirable specular highlight from a single input image is of crucial importance to many computer vision and graphics tasks. Existing methods typically remove specular hi…
Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning
Chaoqun Wang, Xuejin Chen, Shaobo Min +2
Generalized Zero-Shot Learning (GZSL) targets recognizing new categories by learning transferable image representations. Existing methods find that, by aligning image representatio…
Scene text removal via cascaded text stroke detection and erasing
Xuewei Bian, Chaoqun Wang, Weize Quan +3
Recent learning-based approaches show promising performance improvement for scene text removal task. However, these methods usually leave some remnants of text and obtain visually…
Domain-aware Visual Bias Eliminating for Generalized Zero-Shot Learning
Shaobo Min, Hantao Yao, Hongtao Xie +3
Recent methods focus on learning a unified semantic-aligned visual representation to transfer knowledge between two domains, while ignoring the effect of semantic-free visual repre…
CNN Feature boosted SeqSLAM for Real-Time Loop Closure Detection
Dongdong Bai, Chaoqun Wang, Bo Zhang +2
Loop closure detection (LCD) is an indispensable part of simultaneous localization and mapping systems (SLAM); it enables robots to produce a consistent map by recognizing previous…