ConsNet: Learning Consistency Graph for Zero-Shot Human-Object Interaction Detection
Wuhan University（武汉大学）；State University of New York at Buffalo（纽约州立大学布法罗分校）；Peng Cheng Laboratory（鹏城实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））
We consider the problem of Human-Object Interaction (HOI) Detection, which aims to locate and recognize HOI instances in the form of <human, action, object> in images. Most existing works treat HOIs as individual interaction categories, thus can not handle the problem of long-tail distribution and polysemy of action labels. We argue that multi-level consistencies among objects, actions and interactions are strong cues for generating semantic representations of rare or previously unseen HOIs. Leveraging the compositional and relational peculiarities of HOI labels, we propose ConsNet, a knowledge-aware framework that explicitly encodes the relations among objects, actions and interactions into an undirected graph called consistency graph, and exploits Graph Attention Networks (GATs) to propagate knowledge among HOI categories as well as their constituents. Our model takes visual features of candidate human-object pairs and word embeddings of HOI labels as inputs, maps them into visual-semantic joint embedding space and obtains detection results by measuring their similarities. We extensively evaluate our model on the challenging V-COCO and HICO-DET datasets, and results validate that our approach outperforms state-of-the-arts under both fully-supervised and zero-shot settings. Code is available at https://github.com/yeliudev/ConsNet.
InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions
Adobe Research（Adobe研究院）；KAUST（卡塔尔科技大学）；University of Oregon（俄勒冈大学）；University of Memphis（密苏里大学孟菲斯分校）；Johns Hopkins University（约翰霍普金斯大学）；Meta AI；Texas A&M University（德克萨斯农工大学）；Dolby Labs（杜比实验室）；Virginia Tech（弗吉尼亚理工大学）；Cisco（思科）；University of Maryland, College Park（马里兰大学学院市分校）
Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval
Computer Vision Center（计算机视觉中心）；Autonomous University of Barcelona（巴塞罗那自治大学）；Amsterdam Machine Learning Lab（阿姆斯特丹机器学习实验室）；University of Amsterdam（阿姆斯特丹大学）
Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency
Singapore Management University（新加坡管理大学）；South China University of Technology（华南理工大学）；Nanjing University of Science and Technology（南京理工大学）；Cardiff University（卡迪夫大学）
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning
The Hong Kong Polytechnic University（香港理工大学）；Hong Kong Baptist University（香港浸会大学）；Shenzhen University（深圳大学）；Jilin University（吉林大学）；Hong Kong University of Science and Technology（香港科技大学）
Adaptive Semantic Consistency for Cross-domain Few-shot Classification
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）；School of Electronic Information and Communications, Huazhong University of Science and Technology（华中科技大学电子信息与通信学院）
Few-shot Defect Image Generation based on Consistency Modeling
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；CASI Vision Technology CO., LTD.（中科视景科技有限公司）
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, School of Informatics, Xiamen University（中国教育部多媒体可信感知与高效计算重点实验室，厦门大学信息学院）；Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology（厦门理工学院福建省模式识别与图像理解重点实验室）；School of Computer and Information Engineering, Xiamen University of Technology（厦门理工学院计算机与信息工程学院）
Consistency-Regularized GAN for Few-Shot SAR Target Recognition
College of Electronics and Information Engineering, Wuyi University（威夷大学电子与信息工程学院）；College of Electronic and Information Engineering, South China University of Technology（华南理工大学电子与信息工程学院）；Department of Geography, The University of Hong Kong（香港大学地理系）；Faculty of Innovation Engineering, Macau University of Science and Technology（澳门科技大学创新工程学院）；Faculty of Computer Science and Engineering, South China University of Technology（华南理工大学计算机科学与工程学院）
Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
University of Amsterdam（阿姆斯特丹大学）；Mohamed Bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Inception Institute of Artificial Intelligence（起源人工智能研究院）
StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields
Nanyang Technological University（南洋理工大学）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）；University of Ottawa（渥太华大学）；Carnegie Mellon University（卡内基梅隆大学）；MBZUAI（穆罕默德·本·扎耶德人工智能大学）
Visual Prompting for One-shot Controllable Video Editing without Inversion
Singapore University of Technology and Design（新加坡科技设计大学）；Wuhan University（武汉大学）；Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore（新加坡资讯与通信研究院）
FAGStyle: Feature Augmentation on Geodesic Surface for Zero-shot Text-guided Diffusion Image Style Transfer
School of Computer Engineering and Science, Shanghai University（上海大学计算机工程与科学学院）；Key Laboratory of Silicate Cultural Relics Conservation (Shanghai University), Ministry of Education（教育部硅酸盐文物保护重点实验室（上海大学））
Zero-Shot Video Restoration and Enhancement with Text-to-Image Latent Diffusion Models and Multi-Modal References
School of Electrical and Information Engineering, Tianjin University（天津大学电气自动化与信息工程学院）；Lappeenranta-Lahti University of Technology LUT（拉彭兰塔-拉赫蒂理工大学（LUT））
Zero-Shot Video Restoration and Enhancement with Assistance of Video Diffusion Models
School of Electrical and Information Engineering, Tianjin University（电子信息工程学院，天津大学）；Computer Vision and Pattern Recognition Laboratory, School of Engineering Science, Lappeenranta-Lahti University of Technology LUT（计算机视觉与模式识别实验室，工程科学学院，拉佩兰塔-拉赫蒂技术大学LUT）
Consistency-Driven Calibration and Matching for Few-Shot Class-Incremental Learning
School of Automation, Central South University, China（中南大学自动化学院）；Big Data Institute, Central South University, China（中南大学大数据研究院）；School of Computer Science, Faculty of Engineering, The University of Sydney, Australia（悉尼大学工程学院计算机科学系）
Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models
Guangdong Institute of Intelligence Science and Technology（广东智能科学与技术研究院）；Agency for Science, Technology and Research（科技研究局）；School of Information Technology（信息技术学院）
ANYPORTAL: Zero-Shot Consistent Video Background Replacement
Wangxuan Institute of Computer Technology, State Key Laboratory of Multimedia Information Processing, Peking University, Beijing, China（王轩计算机技术研究所，多媒体信息处理国家重点实验室，北京大学，北京）
ConsistNav: Closing the Action Consistency Gap in Zero-Shot Object Navigation with Semantic Executive Control
Sun Yat-sen University（中山大学）；The University of Hong Kong（香港大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））；City University of Hong Kong（香港城市大学）；Carnegie Mellon University（卡内基梅隆大学）
ConsDreamer: Advancing Multi-View Consistency for Zero-Shot Text-to-3D Generation
School of Artificial Intelligence, Nanjing University of Information Science and Technology（南京信息工程大学人工智能学院）；Department of Automation, Tsinghua University（清华大学自动化系）；Lenovo（联想）
