This paper addresses key challenges in object-centric representation learning of video. While existing approaches struggle with complex scenes, we propose a novel weakly-supervised framework that emphasises geometric understanding and leverages pre-trained vision models to enhance object discovery. Our method introduces an efficient slot decoder specifically designed for object-centric learning, enabling effective representation of multi-object scenes without requiring explicit depth information. Results on synthetic video benchmarks with increasing complexity in terms of objects and their movement, object occlusion and camera motion demonstrate that our approach achieves comparable performance to supervised methods while maintaining computational efficiency. This advances the field towards more practical applications in complex real-world scenarios.
Last-Layer-Centric Feature Recombination: Unleashing 3D Geometric Knowledge in DINOv3 for Monocular Depth Estimation
Princeton University（普林斯顿大学）；Springer Heidelberg（斯普林格海德堡）；ABC Institute（ABC研究所）；Aerospace Information Research Institute Chinese Academy of Sciences（中国科学院航天信息研究所）
Object-Uni: A Unified Model for Object-Centric Spatial Understanding and Controllable Generation
School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；MAIS, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所MAIS）；School of Vehicle and Mobility, Tsinghua University（清华大学车辆与 mobility学院）；Ant Group（蚂蚁集团）
Geometric-Guided Few-Shot Dental Landmark Detection with Human-Centric Foundation Model
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China（电子与计算机工程系，香港科学与技术大学）；Division of Paediatric Dentistry and Orthodontics, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China（牙科学院儿童牙科与正畸学系，香港大学）
PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling
Department of Computer Science, City University of Hong Kong（香港城市大学计算机科学系）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）
FindAnything: Open-Vocabulary and Object-Centric Mapping for Robot Exploration in Any Environment
Technical University of Munich（技术大学慕尼黑）；School of Computation, Information and Technology（计算、信息与技术学院）；ETH Zurich（苏黎世联邦理工学院）；Department of Computing（计算学院）；Imperial College London（伦敦帝国理工学院）；University of Patras（帕特拉大学）；Munich Institute of Robotics and Machine Intelligence (MIRMI)（慕尼黑机器人与机器智能研究所）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）
TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching
Dept. of Mechanical Engineering, SNU（机械工程系，首尔国立大学）；Oxford Robotics Institute, University of Oxford（牛津大学机器人研究所）；CSIRO Robotics, DATA61, CSIRO and the School of Electrical Engineering and Computer Science, The University of Queensland (UQ)（CSIRO机器人、DATA61、CSIRO及昆士兰大学电气工程与计算机科学学院）
Point Linguist Model: Segment Any Object via Bridged Large 3D-Language Model
Department of Computer Science, Aberystwyth University（计算机科学系，阿伯里斯特维斯大学）；School of Computer Science, University of Sheffield（计算机科学学院，谢菲尔德大学）；Department of Automation, Tsinghua University（自动化系，清华大学）
EvObj: Learning Evolving Object-centric Representations for 3D Instance Segmentation without Scene Supervision
Shenzhen Research Institute, The Hong Kong Polytechnic University（深圳研究 institute，香港理工大学）；vLAR Group, The Hong Kong Polytechnic University（vLAR 团队，香港理工大学）
UniScene: Unified Occupancy-centric Driving Scene Generation
Shanghai Jiao Tong University（上海交通大学）；Ningbo Institute of Digital Twin, Eastern Institute of Technology（东方理工大学宁波数字孪生研究院）；Tsinghua University（清华大学）；MEGVII Technology（旷视科技）；Mach Drive（马赫驱动）；Fudan University（复旦大学）；University of Hong Kong（香港大学）
A Hyperbolic Perspective on Hierarchical Structure in Object-Centric Scene Representations
Aalborg University & Pioneer Centre for AI, Denmark（奥尔堡大学 & 人工智能先锋中心，丹麦）；Universitat de Barcelona & Computer Vision Center, Spain（巴塞罗那大学 & 计算机视觉中心，西班牙）；Milestone Systems, Denmark（Milestone Systems，丹麦）；University of Guelph & Vector Institute, Canada（圭尔夫大学 & 向量研究所，加拿大）
SuperOcc: Toward Cohesive Temporal Modeling for Superquadric-based 3D Occupancy Prediction
School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China（大连理工大学控制科学与工程学院，大连 116024，中国）；Dalian Rail Transmit Intelligent Control and Intelligent Operation Technology Innovation Center, Dalian 116024, China（大连铁路传输智能控制与智能运维技术创新中心，大连 116024，中国）；Dalian Seasky Automation Co., Ltd, Dalian 116024, China（大连海 sky 自动化有限公司，大连 116024，中国）
On the Geometric Accuracy of Implicit and Primitive-based Representations Derived from View Rendering Constraints
KU Leuven, Dept. Electrical Engineering, Research unit Processing Speech and Images（KU莱顿，电气工程系，语音与图像研究单位）；UCLouvain, ICTEAM, Dept. Electrical Engineering（UCLouvain，ICTEAM，电气工程系）；KU Leuven, Dept. Mechanical Engineering, Research unit Robotics, Automation and Mechatronics（KU莱顿，机械工程系，机器人、自动化与机电研究单位）
