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arXiv 2103.01128cs.CV
InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
The Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；Shenzhen Research Institute of Big Data（深圳大数据研究院）；Southern University of Science and Technology（南方科技大学）
Compared with the visual grounding on 2D images, the natural-language-guided 3D object localization on point clouds is more challenging. In this paper, we propose a new model, named InstanceRefer, to achieve a superior 3D visual grounding through the grounding-by-matching strategy. In practice, our model first predicts the target category from the language descriptions using a simple language classification model. Then, based on the category, our model sifts out a small number of instance candidates (usually less than 20) from the panoptic segmentation of point clouds. Thus, the non-trivial 3D visual grounding task has been effectively re-formulated as a simplified instance-matching problem, considering that instance-level candidates are more rational than the redundant 3D object proposals. Subsequently, for each candidate, we perform the multi-level contextual inference, i.e., referring from instance attribute perception, instance-to-instance relation perception, and instance-to-background global localization perception, respectively. Eventually, the most relevant candidate is selected and localized by ranking confidence scores, which are obtained by the cooperative holistic visual-language feature matching. Experiments confirm that our method outperforms previous state-of-the-arts on ScanRefer online benchmark and Nr3D/Sr3D datasets.
From Objects to Anywhere: A Holistic Benchmark for Multi-level Visual Grounding in 3D Scenes
State Key Laboratory of General Artificial Intelligence, BIGAI（通用人工智能国家重点实验室，BIGAI）；Tsinghua University（清华大学）；Peking University（北京大学）；Beijing Institute of Technology（北京理工大学）
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）
University of Science and Technology of China（中国科学技术大学）；Nanyang Technological University（南洋理工大学）；Hefei University of Technology（合肥工业大学）；Singapore Management University（新加坡管理大学）
HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person Scenarios
Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；Beijing Institute of Technology（北京理工大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Hunan University（湖南大学）；Shanghai AI Lab（上海人工智能实验室）；HEBUST
Mohamed bin Zayed University of AI（穆罕默德·本·扎耶德人工智能大学）；Australian National University（澳大利亚国立大学）；Aalto University（阿尔托大学）；Carnegie Mellon University（卡内基梅隆大学）；University of California - Merced（加州大学默塞德分校）；Linköping University（林雪平大学）；Google Research（谷歌研究院）
GeoChat: Grounded Large Vision-Language Model for Remote Sensing
Mohamed bin Zayed University of AI（穆罕默德·本·扎耶德人工智能大学）；Birla Institute of Technology & Science, Hyderabad（海得拉巴贝拉理工学院）；Australian National University（澳大利亚国立大学）；Linköping University（林雪平大学）
Cognitive Disentanglement for Referring Multi-Object Tracking
Qingdao Institute of Software, College of Computer Science and Technology, China University of Petroleum (East China)（青岛软件研究所，计算机科学与技术学院，中国石油大学（华东））；Thrust of AI, Hong Kong University of Science and Technology (GuangZhou)（人工智能研究组，香港科学与技术大学（广州））；Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software（山东省智能油气工业软件重点实验室）；Wangxuan Institute of Computer Technology, Peking University（王轩计算机技术研究所，北京大学）；School of Automation, Southeast University（自动化学院，东南大学）；School of Computer Science, Beijing Institute of Technology（计算机科学学院，北京理工大学）；School of Artificial Intelligence and Computer Science, Nantong University（人工智能与计算机科学学院，南通大学）；Thrust of Intelligent Transportation, Hong Kong University of Science and Technology (GuangZhou)（智能交通研究组，香港科学与技术大学（广州））；Department of Electrical Engineering and Electronics, University of Liverpool（电子工程与电子学院，利物浦大学）
EarthGPT-X: A Spatial MLLM for Multi-level Multi-Source Remote Sensing Imagery Understanding with Visual Prompting
School of Interdisciplinary Science, Beijing Institute of Technology（交叉科学学院，北京理工大学）；College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing, Beijing Institute of Technology（空间智能信息处理国家重点实验室，北京理工大学）；School of Optics and Photonics, Beijing Institute of Technology（光学与 photonics 学院，北京理工大学）；State Key Laboratory of Explosion Science and Safety Protection, Beijing（爆炸科学与安全防护国家重点实验室，北京）
Deforming Videos to Masks: Flow Matching for Referring Video Segmentation
SGIT AI Lab, State Grid Corporation of China（国网信通研究院）；University of California, San Diego（加州大学圣地亚哥分校）；The Hong Kong University of Science and Technology（香港科技大学）；The University of Tokyo（东京大学）；University of Cambridge（剑桥大学）；Zhejiang University of Technology（浙江工业大学）；Baidu（百度）
RefAtomNet++: Advancing Referring Atomic Video Action Recognition using Multi-Trajectory Semantic Retrieval
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（人机化研究所，卡尔斯鲁厄技术大学）；RISE Research Institutes of Sweden（瑞典RISE研究机构）；KTH Royal Institute of Technology（皇家理工学院）；School of Artificial Intelligence and Robotics（人工智能与机器人学院）；National Engineering Research Center of Robot Visual Perception and Control Technology（机器人视觉感知与控制技术国家工程研究中心）；Chinese University of Hong Kong（香港中文大学）；Shanghai AI Lab（上海人工智能实验室）
