Generating longer textual sequences when conditioned on the visual information is an interesting problem to explore. The challenge here proliferate over the standard vision conditioned sentence-level generation (e.g., image or video captioning) as it requires to produce a brief and coherent story describing the visual content. In this paper, we mask this Vision-to-Sequence as Graph-to-Sequence learning problem and approach it with the Transformer architecture. To be specific, we introduce Sparse Graph-to-Sequence Transformer (SGST) for encoding the graph and decoding a sequence. The encoder aims to directly encode graph-level semantics, while the decoder is used to generate longer sequences. Experiments conducted with the benchmark image paragraph dataset show that our proposed achieve 13.3% improvement on the CIDEr evaluation measure when comparing to the previous state-of-the-art approach.
TEVI: Text-Conditioned Editing of Visual Representations via Sparse Autoencoders for Improved Vision-Language Alignment
Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany（马克斯·普朗克研究所信息学院，萨尔兰信息学院，德国萨尔布吕肯）；Department of Language Science and Technology, Saarland University, Saarbrücken, Germany（语言科学与技术系，萨尔兰大学，德国萨尔布吕肯）
AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit Representations
University of Konstanz（康斯坦茨大学）
本文介绍了注意隐式表示网络（AIR-Nets），这是一种简单但高效的点云三维重建架构。由于以局部和模块化方式表示3D形状可以提高泛化和重建质量，因此AIR-Nets将输入点云编码为一组锚定在3D空间中的局部潜在向量，这些向量局部描述对象的几何形状，以及全局潜在描述，从而实现全局一致性。我们的模型是第一个无网格的，基于编码器的方法，局部描述了一个隐式函数。来自[Zhao et al. 2020]的向量注意力机制作为主要的点云处理模块，并允许排列不变性和平移等变性。当用3D坐标查询时，我们的解码器从全局和附近的局部隐向量中收集信息，以预测占用值。ShapeNet数据集上的实验表明，AIR-Nets的性能明显优于以前最先进的基于编码器的隐式形状学习方法，尤其是在稀疏设置中占主导地位。此外，我们的模型在zero-shot设置中很好地推广到FAUST数据集。最后，由于AIR-Nets使用稀疏的潜在表示并遵循简单的操作方案，因此该模型为未来的工作提供了几个现有的途径。我们的代码可在https://github.com/SimonGiebenhain/AIR-Nets上获得。
TNT: Text-Conditioned Network with Transductive Inference for Few-Shot Video Classification
Pontificia Universidad Católica de Chile（智利天主教大学）；Samsung AI Centre Cambridge（三星人工智能中心剑桥）；Stanford University（斯坦福大学）；KU Leuven（鲁汶大学）；Facebook AI（Facebook 人工智能）
ReCo-Diff: Residual-Conditioned Deterministic Sampling for Cold Diffusion in Sparse-View CT
National Institute for Mathematical Sciences, Daejeon, 34047, Republic of Korea（韩国全南数学研究所）；Department of Computer Engineering, Korea National University of Transportation, Chungju, 27469, Republic of Korea（韩国交通国立大学计算机工程系）
Text-Audio-Visual-conditioned Diffusion Model for Video Saliency Prediction
School of Computer Science, Nanjing University of Information Science and Technology（信息科学与技术南京大学计算机科学学院）；Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology（大气环境与设备技术江苏省协同创新中心）；School of Computer Science and Informatics, Cardiff University（计算机科学与信息学院卡斯尔大学）；Faculty of Information Technology and Communication Sciences, Tampere University（信息科技与通讯科学学院坦佩雷大学）
MGCR-Net:Multimodal Graph-Conditioned Vision-Language Reconstruction Network for Remote Sensing Change Detection
School of Computer Science and Technology, Shandong Technology and Business University（山东科技职业大学计算机科学与技术学院）；School of Computer Science and Technology, Qingdao University（青岛大学计算机科学与技术学院）；School 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）
Observation-Conditioned Latent Energy Priors for Sparse Implicit Neural Shape Completion
University of Zurich（苏黎世大学）；University Hospital Zurich（苏黎世大学医院）；ETH Zurich（苏黎世联邦理工学院）；Technical University of Munich（慕尼黑工业大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）
CloseUpShot: Close-up Novel View Synthesis from Sparse-views via Point-conditioned Diffusion Model
Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)（深圳未来网络智能研究院（FNii-深圳））；Chinese University of Hong Kong at Shenzhen (CUHKSZ)（香港中文大学（深圳））；Sun Yat-sen University（中山大学）
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
Multimodal-Conditioned Latent Diffusion Models for Fashion Image Editing
Media Integration and Communication Center (MICC), University of Florence（佛罗伦萨大学媒体集成与传播中心（MICC））；University of Florence（佛罗伦萨大学）；University of Modena and Reggio Emilia（摩德纳-雷焦艾米利亚大学）；University of Pisa（比萨大学）
MoSAT: Human Motion Generation from Spatial Audio and Textual Description
The University of Hong Kong（香港大学）；Massachusetts Institute of Technology（麻省理工学院）；University of Pennsylvania（宾夕法尼亚大学）；Brown University（布朗大学）；Shanghai AI Lab（上海人工智能实验室）；Macau University of Science and Technology（澳门科技大学）；Hong Kong University of Science and Technology（香港科技大学）；Texas A&M University（德克萨斯农工大学）
LODE: Locally Conditioned Eikonal Implicit Scene Completion from Sparse LiDAR
Tsinghua University（清华大学）；Institute for AI Industry Research (AIR), Tsinghua University（清华大学智能产业研究院（AIR））；University of Chinese Academy of Sciences（中国科学院大学）
Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy（人工智能与计算机系统单位，工程系，罗马生物医学大学）
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation
College of Information and Electrical Engineering, China Agricultural University（中国农业大学信息与电气工程学院）；Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University（中国农业大学北京农业物联网工程技术研究中心）；School of Electronic and Computer Engineering, Peking University（北京大学电子与计算机工程学院）；Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；School of Engineering, The Hong Kong University of Science and Technology（香港科技大学工程学院）；Department of Electrical Engineering, Yale University（耶鲁大学电气工程系）
Geo-EVS: Geometry-Conditioned Extrapolative View Synthesis for Autonomous Driving
School of Vehicle and Mobility, Tsinghua University（清华大学车辆与运载学院）；State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University（清华大学智能绿色车辆与移动国家重点实验室）；School of Science, Minzu University（中央民族大学理学院）；Chongqing Changan Automobile Co., Ltd.（重庆长安汽车股份有限公司）
Spatial-Related Sensors Matters: 3D Human Motion Reconstruction Assisted with Textual Semantics
Beijing Advanced Innovation Center for Materials Genome Engineering（北京材料基因组工程先进创新中心）；University of Science and Technology Beijing（北京科技大学）；Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education（智能仿生无人系统教育部重点实验室）；Institute of Materials Intelligent Technology, Liaoning Academy of Materials（辽宁材料实验室材料智能技术研究所）
AULLM++: Structured-Token-Conditioned Large Language Models for Micro-Expression Action Unit Detection
Great Bay University（广东东莞大学）；Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
MoE Key Lab of Artificial Intelligence, AI Institute, School of Computer Science, Shanghai Jiao Tong University（人工智能大模型重点实验室、人工智能学院、计算机科学学院、上海交通大学）；Huawei Inc.（华为公司）；Huazhong University of Science and Technology（华中科技大学）
