Referring video object segmentation (RVOS) aims to segment the target object in a video sequence described by a language expression. Typical multimodal Transformer based RVOS approaches process video sequence in a frame-independent manner to reduce the high computational cost, which however restricts the performance due to the lack of inter-frame interaction for temporal coherence modeling and spatio-temporal representation learning of the referred object. Besides, the absence of sufficient cross-modal interactions results in weak correlation between the visual and linguistic features, which increases the difficulty of decoding the target information and limits the performance of the model. In this paper, we propose a bidirectional correlation-driven inter-frame interaction Transformer, dubbed BIFIT, to address these issues in RVOS. Specifically, we design a lightweight and plug-and-play inter-frame interaction module in the Transformer decoder to efficiently learn the spatio-temporal features of the referred object, so as to decode the object information in the video sequence more precisely and generate more accurate segmentation results. Moreover, a bidirectional vision-language interaction module is implemented before the multimodal Transformer to enhance the correlation between the visual and linguistic features, thus facilitating the language queries to decode more precise object information from visual features and ultimately improving the segmentation performance. Extensive experimental results on four benchmarks validate the superiority of our BIFIT over state-of-the-art methods and the effectiveness of our proposed modules.
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）
Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation
School of Electronics and Information Engineering, Harbin Institute of Technology（电子信息工程学院，哈尔滨工业大学）；Faculty of Computing, Harbin Institute of Technology（计算机学院，哈尔滨工业大学）；Peng Cheng Laboratory, Shenzhen（鹏城实验室，深圳）
EchoTrack: Auditory Referring Multi-Object Tracking for Autonomous Driving
College of Computer Science and Electronic Engineering, Hunan University（湖南大学计算机与电子工程学院）；School of Robotics, Hunan University（湖南大学机器人学院）；National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University（湖南大学机器人视觉感知与控制技术国家工程研究中心）；Institute for Robotics and Anthropomatics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院机器人与人类工程学研究所）；Hangzhou SurImage Technology Company Ltd.（杭州 SurImage 科技有限公司）
OneRef: Unified One-tower Expression Grounding and Segmentation with Mask Referring Modeling
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Pengcheng Laboratory（鹏城实验室）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））
CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention
Wuhan University of Technology（武汉理工大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；MedAI Technology (Wuxi) Co. Ltd.（MedAI科技（无锡）有限公司）；Technical University of Munich（慕尼黑工业大学）
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）
Progressive Prompt-Guided Cross-Modal Reasoning for Referring Image Segmentation
School of Computer Science and Artificial Intelligence, Wuhan University of Technology（武汉理工大学计算机科学与人工智能学院）；School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（华中科技大学人工智能与自动化学院）；University of Electronic Science and Technology of China（电子科技大学）；Wuhan Vocational College of Software and Engineering（武汉软件工程职业学院）
Intra- and Cross-Scale Feature Interaction Network for Referring Remote Sensing Image Segmentation
School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University（人工智能、光学与电子学院（iOPEN），西北工业大学）；School of Computer Science, Northwestern Polytechnical University（计算机科学学院，西北工业大学）；department of Software, Northwest Institute of Nuclear Technology（软件系，西北核技术研究院）
Exploring Fine-Grained Image-Text Alignment for Referring Remote Sensing Image Segmentation
School of Information Science and Technology, Southwest Jiaotong University（西南交通大学信息科学与技术学院）；Ant Group（蚂蚁集团）；Luoyang Institute of Electro-optical Equipment, AVIC（中国航空工业集团公司洛阳电光设备研究所）；Faculty of Geosciences and Engineering, Southwest Jiaotong University（西南交通大学地球科学与环境工程学院）
