106 citations · 113 across the 17 of their papers we have counts for
20 papers
Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?
Caixin Kang, Tianyu Yan, Sitong Gong +8
Multimodal Large Language Models (MLLMs) are increasingly deployed in human-facing roles where personality perception is critical, yet existing benchmarks evaluate this capability…
ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning
Yuan Zhao, Youwei Pang, Jiaming Zuo +10
Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the notion of a concept remains…
Rethinking Evaluation of Infrared Small Target Detection
Youwei Pang, Xiaoqi Zhao, Lihe Zhang +4
As an essential vision task, infrared small target detection (IRSTD) has seen significant advancements through deep learning. However, critical limitations in current evaluation pr…
UniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
Xiaoqi Zhao, Youwei Pang, Chenyang Yu +5
Multi-modal image segmentation faces real-world deployment challenges from incomplete/corrupted modalities degrading performance. While existing methods address training-inference…
UniMMAD: Unified Multi-Modal and Multi-Class Anomaly Detection via MoE-Driven Feature Decompression
Yuan Zhao, Youwei Pang, Lihe Zhang +4
Existing anomaly detection (AD) methods often treat the modality and class as independent factors. Although this paradigm has enriched the development of AD research branches and p…
Referring Remote Sensing Image Segmentation with Cross-view Semantics Interaction Network
Jiaxing Yang, Lihe Zhang, Huchuan Lu
Recently, Referring Remote Sensing Image Segmentation (RRSIS) has aroused wide attention. To handle drastic scale variation of remote targets, existing methods only use the full im…
Power Battery Detection
Xiaoqi Zhao, Peiqian Cao, Chenyang Yu +10
Power batteries are essential components in electric vehicles, where internal structural defects can pose serious safety risks. We conduct a comprehensive study on a new task, powe…
UniSegDiff: Boosting Unified Lesion Segmentation via a Staged Diffusion Model
Yilong Hu, Shijie Chang, Lihe Zhang +3
The Diffusion Probabilistic Model (DPM) has demonstrated remarkable performance across a variety of generative tasks. The inherent randomness in diffusion models helps address issu…
EffOWT: Transfer Visual Language Models to Open-World Tracking Efficiently and Effectively
Bingyang Wang, Kaer Huang, Bin Li +4
Open-World Tracking (OWT) aims to track every object of any category, which requires the model to have strong generalization capabilities. Trackers can improve their generalization…
Inspiring the Next Generation of Segment Anything Models: Comprehensively Evaluate SAM and SAM 2 with Diverse Prompts Towards Context-Dependent Concepts under Different Scenes
Xiaoqi Zhao, Youwei Pang, Shijie Chang +10
As large-scale foundation models trained on billions of image--mask pairs covering a vast diversity of scenes, objects, and contexts, SAM and its upgraded version, SAM~2, have sign…
Adversarial Training: A Survey
Mengnan Zhao, Lihe Zhang, Jingwen Ye +3
Adversarial training (AT) refers to integrating adversarial examples -- inputs altered with imperceptible perturbations that can significantly impact model predictions -- into the…
High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity
Qian Yu, Peng-Tao Jiang, Hao Zhang +4
In the realm of high-resolution (HR), fine-grained image segmentation, the primary challenge is balancing broad contextual awareness with the precision required for detailed object…
High-Performance Few-Shot Segmentation with Foundation Models: An Empirical Study
Shijie Chang, Lihe Zhang, Huchuan Lu
Existing few-shot segmentation (FSS) methods mainly focus on designing novel support-query matching and self-matching mechanisms to exploit implicit knowledge in pre-trained backbo…
Beyond Mask: Rethinking Guidance Types in Few-shot Segmentation
Shijie Chang, Youwei Pang, Xiaoqi Zhao +2
Existing few-shot segmentation (FSS) methods mainly focus on prototype feature generation and the query-support matching mechanism. As a crucial prompt for generating prototype fea…
Spider: A Unified Framework for Context-dependent Concept Segmentation
Xiaoqi Zhao, Youwei Pang, Wei Ji +4
Different from the context-independent (CI) concepts such as human, car, and airplane, context-dependent (CD) concepts require higher visual understanding ability, such as camoufla…
Spatial Semantic Recurrent Mining for Referring Image Segmentation
Jiaxing Yang, Lihe Zhang, Jiayu Sun +1
Referring Image Segmentation (RIS) consistently requires language and appearance semantics to more understand each other. The need becomes acute especially under hard situations. T…
Multi-view Aggregation Network for Dichotomous Image Segmentation
Qian Yu, Xiaoqi Zhao, Youwei Pang +2
Dichotomous Image Segmentation (DIS) has recently emerged towards high-precision object segmentation from high-resolution natural images. When designing an effective DIS model, the…
Towards Automatic Power Battery Detection: New Challenge, Benchmark Dataset and Baseline
Xiaoqi Zhao, Youwei Pang, Zhenyu Chen +5
We conduct a comprehensive study on a new task named power battery detection (PBD), which aims to localize the dense cathode and anode plates endpoints from X-ray images to evaluat…
Open-Vocabulary Camouflaged Object Segmentation
Youwei Pang, Xiaoqi Zhao, Jiaming Zuo +2
Recently, the emergence of the large-scale vision-language model (VLM), such as CLIP, has opened the way towards open-world object perception. Many works have explored the utilizat…
ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection
Youwei Pang, Xiaoqi Zhao, Tian-Zhu Xiang +2
Recent camouflaged object detection (COD) attempts to segment objects visually blended into their surroundings, which is extremely complex and difficult in real-world scenarios. Ap…