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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition"
23240 条 记 录,以下是111-120 订阅
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Attention-Propagation Network for Egocentric Heatmap to 3D Pose Lifting
Attention-Propagation Network for Egocentric Heatmap to 3D P...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kang, Taeho Lee, Youngki Seoul Natl Univ Seoul South Korea
We present EgoTAP, a heatmap-to-3D pose lifting method for highly accurate stereo egocentric 3D pose estimation. Severe self-occlusion and out-of-view limbs in egocentric camera views make accurate pose estimation a c... 详细信息
来源: 评论
eTraM: Event-based Traffic Monitoring Dataset
eTraM: Event-based Traffic Monitoring Dataset
收藏 引用
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
Rugby Scene Classification Enhanced by vision Language Model
Rugby Scene Classification Enhanced by Vision Language Model
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Nonaka, Naoki Fujihira, Ryo Koshiba, Toshiki Maeda, Akira Seita, Jun RIKEN Informat R&D & Strategy Headquarters Adv Data Sci Project Wako Saitama Japan Hakata Knee & Sports Clin Fukuoka Japan
This study investigates the integration of vision language models (VLM) to enhance the classification of situations within rugby match broadcasts. The importance of accurately identifying situations in sports videos i... 详细信息
来源: 评论
Intrinsic Image Diffusion for Indoor Single-view Material Estimation
Intrinsic Image Diffusion for Indoor Single-view Material Es...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kocsis, Peter Sitzmann, Vincent Niessner, Matthias Tech Univ Munich Munich Germany MIT EECS Cambridge MA 02139 USA
We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, an... 详细信息
来源: 评论
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Khanna, Mukul Ramrakhya, Ram Chhablani, Gunjan Yenamandra, Sriram Gervet, Theophile Chang, Matthew Kiraly, Zsolt Chaplot, Devendra Singh Batra, Dhruv Mottaghi, Roozbeh Georgia Inst Technol Atlanta GA 30332 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Illinois Urbana IL USA Mistral AI Paris France Univ Washington Seattle WA USA
The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images. However, these navigation models often handle only ... 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
PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs
PIN: Positional Insert Unlocks Object Localisation Abilities...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Dorkenwald, Michael Barazani, Nimrod Snoek, Cees G. M. Asano, Yuki M. Univ Amsterdam Amsterdam Netherlands
vision-Language Models (VLMs), such as Flamingo and GPT-4V, have shown immense potential by integrating large language models with vision systems. Nevertheless, these models face challenges in the fundamental computer... 详细信息
来源: 评论
Mitigating Object Hallucinations in Large vision-Language Models through Visual Contrastive Decoding
Mitigating Object Hallucinations in Large Vision-Language Mo...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Leng, Sicong Zhang, Hang Chen, Guanzheng Li, Xin Lug, Shijian Miao, Chunyan Bing, Lidong Alibaba Grp DAMO Acad Hangzhou Peoples R China Nanyang Technol Univ Singapore Singapore Hupan Lab Hangzhou 310023 Peoples R China
Large vision-Language Models (LVLMs) have advanced considerably, intertwining visual recognition and language understanding to generate content that is not only coherent but also contextually attuned. Despite their su... 详细信息
来源: 评论
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yang, Julia Barnett, Alina Jade Donnelly, Jon Kishore, Satvik Fang, Jerry Schwartz, Fides Regina Chen, Chaofan Lo, Joseph Y. Rudin, Cynthia Duke Univ Durham NC 27708 USA Brigham & Womens Hosp 75 Francis St Boston MA 02115 USA Univ Maine Orono ME USA
Digital mammography is essential to breast cancer detection, and deep learning offers promising tools for faster and more accurate mammogram analysis. In radiology and other high-stakes environments, uninterpretable (... 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