SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）；National Technical University of Athens（雅典国立技术大学）；Universitat Oberta de Catalunya（加泰罗尼亚开放大学）；Barcelona Supercomputing Center（巴塞罗那超级计算中心）；University of Stuttgart（斯图加特大学）
Ioannis Kazakos, Carles Ventura, Miriam Bellver, Carina Silberer, Xavier Giro-i-Nieto
Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation. However, collecting large datasets for these tasks is expensive in terms of annotation time, which represents a bottleneck. To this end, we propose a novel method, namely SynthRef, for generating synthetic referring expressions for target objects in an image (or video frame), and we also present and disseminate the first large-scale dataset with synthetic referring expressions for video object segmentation. Our experiments demonstrate that by training with our synthetic referring expressions one can improve the ability of a model to generalize across different datasets, without any additional annotation cost. Moreover, our formulation allows its application to any object detection or segmentation dataset.
Proxy-Embedding as an Adversarial Teacher: An Embedding-Guided Bidirectional Attack for Referring Expression Segmentation Models
National Pilot School of Software, Yunnan University（云南大学软件试点学校）；School of Information Science and Engineering, Yunnan University（云南大学信息科学与工程学院）；Institute of Data Science, National University of Singapore（新加坡国立大学数据科学研究所）
RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation
Barcelona Supercomputing Center（巴塞罗那超级计算中心）；Universitat Oberta de Catalunya（加泰罗尼亚开放大学）；Institute for NLP, University of Stuttgart（斯图加特大学自然语言处理研究所）；Universitat Pompeu Fabra（庞培法布拉大学）；National Technical University of Athens（雅典国立技术大学）；Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）
UniPixel: Unified Object Referring and Segmentation for Pixel-Level Visual Reasoning
The Hong Kong Polytechnic University（香港理工大学）；ARC Lab, Tencent PCG（腾讯PCG ARC实验室）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；vivo Mobile Communication Co.（vivo移动通信公司）；MindWingman Technology (Shenzhen) Co., Ltd.（深圳MindWingman技术有限公司）
EventRR: Event Referential Reasoning for Referring Video Object Segmentation
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；The Hong Kong University of Science and Technology（香港科学与技术大学）；Northwestern Polytechnical University（西北工业大学）
Meta Compositional Referring Expression Segmentation
Singapore University of Technology and Design（新加坡科技设计大学）；ByteDance（字节跳动）；Institute for Infocomm Research（资讯通信研究院）；Centre for Frontier AI Research（前沿人工智能研究中心）
RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
College of Computer Science and Technology, National University of Defense Technology（国防科技大学计算机学院）；School of Computer Science, The University of Sydney（悉尼大学计算机学院）
Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院）；School of Information Engineering, Huzhou Normal University（湖州师范学院信息工程学院）；School of Artificial Intelligence, Nanjing University of Posts and Telecommunications（南京邮电大学人工智能学院）；National Key Laboratory of Tibetan Language Intelligence（藏语智能国家重点实验室）；Zhejiang University（浙江大学）；Beijing Normal University（北京师范大学）
Event-Aware Instructed Assistant for Referring Video Segmentation
Institute of Big Data, College of Computer Science and Artificial Intelligence, Fudan University（复旦大学计算机科学与技术学院大数据研究所）；Institute of Trustworthy Embodied AI, Fudan University（复旦大学可信具身智能研究所）；Shanghai University of Finance and Economics（上海财经大学）
A Unified Mutual Supervision Framework for Referring Expression Segmentation and Generation
The Chinese University of Hong Kong（香港中文大学）；International Digital Economy Academy (IDEA)（国际数字经济研究院（IDEA））；The Hong Kong University of Science and Technology（香港科技大学）；Tsinghua University（清华大学）
指称表达式理解和切分是两个高度相关的任务，它们都是为了根据自然语言表达式识别指称对象。在本文中，我们提出了一种新的多任务协作网络（MCN），以实现联合学习的REC和RES的第一次。在MCN中，RES可以帮助REC实现更好的语言-视觉对齐，而REC可以帮助RES更好地定位所指对象。此外，我们解决了这种多任务设置中的一个关键挑战，即，预测冲突，两个创新的设计，即，一致性能量最大化（CEM）和自适应软非定位抑制（ASNLS）。具体来说，CEM使REC和RES能够通过最大化两个任务之间的一致性能量来关注相似的视觉区域。ASNLS基于REC的预测来抑制RES中不相关区域的响应。为了验证我们的模型，我们在REC和RES的三个基准数据集上进行了广泛的实验，即，RefCOCO、RefCOCO+和RefCOCOg。实验结果报告了MCN在所有现有方法上的显着性能增益，即，最高可达+7.13%for REC和+11.50%for RES over SOTA，这充分证实了我们的模型对于REC和RES联合学习的有效性。
DRAgent: Discriminative Reasoning Agent for Referring Expression Segmentation
School of Computer Science and Technology, Hangzhou Dianzi University（杭州电子科技大学计算机科学与技术学院）；Khoury College of Computer Sciences, Northeastern University（东北大学Khoury计算机科学学院）
IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation
Zhejiang University（浙江大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Ningbo Global Innovation Center, Zhejiang University（浙江大学宁波全球创新中心）；Zhejiang Key Laboratory of Digital-Intelligence Service Technology（浙江省数字智能服务技术重点实验室）
SSP-SAM: SAM with Semantic-Spatial Prompt for Referring Expression Segmentation
School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院）；NExT++ Lab, School of Computing, National University of Singapore（新加坡国立大学计算机学院NExT++实验室）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）
MVGGT: Multimodal Visual Geometry Grounded Transformer for Multiview 3D Referring Expression Segmentation
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University（厦门大学多媒体可信感知与高效计算教育部重点实验室）；Shanghai Innovation Institute（上海创新研究院）；Fudan University（复旦大学）；ByteDance（字节跳动）；Tianjin University of Science and Technology（天津科技大学）
Unveiling Parts Beyond Objects:Towards Finer-Granularity Referring Expression Segmentation
Institute of Automation, Chinese Academy of Sciences (CASIA)（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS)（中国科学院大学人工智能学院）；Beijing Academy of Artificial Intelligence (BAAI)（北京人工智能研究院）；University of Science and Technology Beijing (USTB)（北京科技大学）
CoHD: A Counting-Aware Hierarchical Decoding Framework for Generalized Referring Expression Segmentation
Tsinghua Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；School of EIC, Huazhong University of Science and Technology（华中科技大学电子信息与工程学院）；Tencent TEG（腾讯技术工程事业群）
Cross-Modal Progressive Comprehension for Referring Segmentation
Beihang University（北京航空航天大学）；Chinese Academy of Sciences（中国科学院）；University of Chinese Academy of Sciences（中国科学院大学）；Beijing Jiaotong University（北京交通大学）；Sun Yat-sen University（中山大学）；Pazhou Lab（琶洲实验室）
Understanding What Is Not Said:Referring Remote Sensing Image Segmentation with Scarce Expressions
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China（教育部多媒体可信感知与高效计算重点实验室）；Institute of Artificial Intelligence, Xiamen University（厦门大学人工智能研究院）；Xiamen University（厦门大学）；School of Informatics, Xiamen University（厦门大学信息学院）
