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检索条件"任意字段=2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011"
21099 条 记 录,以下是91-100 订阅
排序:
Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation
Animate Anyone: Consistent and Controllable Image-to-Video S...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Hu, Li Alibaba Grp Inst Intelligent Comp Hangzhou Peoples R China
Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative... 详细信息
来源: 评论
Video2Game: Real-time, Interactive, Realistic and Browser-Compatible Environment from a Single Video
Video2Game: Real-time, Interactive, Realistic and Browser-Co...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Xia, Hongchi Lin, Zhi-Hao Ma, Wei-Chiu Wang, Shenlong Univ Illinois Champaign IL 61820 USA Shanghai Jiao Tong Univ Shanghai Peoples R China Cornell Univ Ithaca NY USA
Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automa... 详细信息
来源: 评论
StyleCineGAN: Landscape Cinemagraph Generation using a Pre-trained StyleGAN
StyleCineGAN: Landscape Cinemagraph Generation using a Pre-t...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Choi, Jongwoo Seo, Kwanggyoon Ashtari, Amirsaman Noh, Junyong Korea Adv Inst Sci & Technol Visual Media Lab Daejeon South Korea
We propose a method that can generate cinemagraphs automatically from a still landscape image using a pre-trained StyleGAN. Inspired by the success of recent unconditional video generation, we leverage a powerful pre-... 详细信息
来源: 评论
eTraM: Event-based Traffic Monitoring Dataset
eTraM: Event-based Traffic Monitoring Dataset
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Verma, Aayush Atul Chakravarthi, Bharatesh Vaghela, Arpitsinh Wei, Hua Yang, Yezhou Arizona State Univ Tempe AZ 85287 USA
Event cameras, with their high temporal and dynamic range and minimal memory usage, have found applications in various fields. However, their potential in static traffic monitoring remains largely unexplored. To facil... 详细信息
来源: 评论
Unsupervised Video Domain Adaptation with Masked Pre-Training and Collaborative Self-Training
Unsupervised Video Domain Adaptation with Masked Pre-Trainin...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Reddy, Arun Paul, William Rivera, Corban Shah, Ketul de Melo, Celso M. Chellappa, Rama Johns Hopkins Univ Baltimore MD 21218 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD USA DEVCOM US Army Res Lab Aberdeen Proving Ground MD USA
In this work, we tackle the problem of unsupervised domain adaptation (UDA) for video action recognition. Our approach, which we call UNITE, uses an image teacher model to adapt a video student model to the target dom... 详细信息
来源: 评论
SpikingResformer: Bridging ResNet and vision Transformer in Spiking Neural Networks
SpikingResformer: Bridging ResNet and Vision Transformer in ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Shi, Xinyu Hao, Zecheng Yu, Zhaofei Peking Univ Inst Artificial Intelligence Beijing Peoples R China Peking Univ Sch Comp Sci Beijing Peoples R China
The remarkable success of vision Transformers in Artificial Neural Networks (ANNs) has led to a growing interest in incorporating the self-attention mechanism and transformer-based architecture into Spiking Neural Net... 详细信息
来源: 评论
Dual Pose-invariant Embeddings: Learning Category and Object-specific Discriminative Representations for recognition and Retrieval
Dual Pose-invariant Embeddings: Learning Category and Object...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Sarkar, Rohan Kak, Avinash Purdue Univ Elect & Comp Engn W Lafayette IN 47907 USA
In the context of pose-invariant object recognition and retrieval, we demonstrate that it is possible to achieve significant improvements in performance if both the category-based and the object-identity-based embeddi... 详细信息
来源: 评论
CONFORM: Contrast is All You Need For High-Fidelity Text-to-Image Diffusion Models
CONFORM: Contrast is All You Need For High-Fidelity Text-to-...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Meral, Tuna Han Salih Simsar, Enis Tombari, Federico Yanardag, Pinar Virginia Tech Blacksburg VA USA Swiss Fed Inst Technol Zurich Switzerland TUM Munich Germany Google Menlo Pk CA USA
Images produced by text-to-image diffusion models might not always faithfully represent the semantic intent of the provided text prompt, where the model might overlook or entirely fail to produce certain objects. Exis... 详细信息
来源: 评论
Improving Visual recognition with Hyperbolical Visual Hierarchy Mapping
Improving Visual Recognition with Hyperbolical Visual Hierar...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kwon, Hyeongjun Jang, Jinhyun Kim, Jin Kim, Kwonyoung Sohn, Kwanghoon Yonsei Univ Seoul South Korea Korea Inst Sci & Technol KIST Seoul South Korea
Visual scenes are naturally organized in a hierarchy, where a coarse semantic is recursively comprised of several fine details. Exploring such a visual hierarchy is crucial to recognize the complex relations of visual... 详细信息
来源: 评论
Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
Telling Left from Right: Identifying Geometry-Aware Semantic...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhang, Junyi Herrmann, Charles Hur, Junhwa Chen, Eric Jampani, Varun Sun, Deqing Yang, Ming-Hsuan Shanghai Jiao Tong Univ Shanghai Peoples R China Google Res Mountain View CA USA UIUC Champaign IL USA Stabil AI London England UC Merced Merced CA USA
While pre-trained large-scale vision models have shown significant promise for semantic correspondence, their features often struggle to grasp the geometry and orientation of instances. This paper identifies the impor... 详细信息
来源: 评论