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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191-200 订阅
排序:
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetr...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Turki, Haithem Agrawal, Vasu Bulo, Samuel Rota Porzi, Lorenzo Kontschieder, Peter Ramanan, Deva Zollhofer, Michael Richardt, Christian Meta Real Labs Menlo Pk CA 94025 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA
Neural radiance fields provide state-of-the-art view synthesis quality but tend to be slow to render. One reason is that they make use of volume rendering, thus requiring many samples (and model queries) per ray at re... 详细信息
来源: 评论
Exploring the Zero-Shot Capabilities of vision-Language Models for Improving Gaze Following
Exploring the Zero-Shot Capabilities of Vision-Language Mode...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Gupta, Anshul Vuillecard, Pierre Farkhondeh, Arya Odobez, Jean-Marc Idiap Res Inst Martigny Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland
Contextual cues related to a person's pose and interactions with objects and other people in the scene can provide valuable information for gaze following. While existing methods have focused on dedicated cue extr... 详细信息
来源: 评论
SonicvisionLM: Playing Sound with vision Language Models
SonicVisionLM: Playing Sound with Vision Language Models
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Xie, Zhifeng Yu, Shengye He, Qile Li, Mengtian Shanghai Univ Shanghai Peoples R China Shanghai Engn Res Ctr Mot Picture Special Effects Shanghai Peoples R China
There has been a growing interest in the task of generating sound for silent videos, primarily because of its practicality in streamlining video post-production. However, existing methods for video-sound generation at... 详细信息
来源: 评论
Segment Anything Model for Road Network Graph Extraction
Segment Anything Model for Road Network Graph Extraction
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hetang, Congrui Xue, Haoru Le, Cindy Yue, Tianwei Wang, Wenping He, Yihui Carnegie Mellon Univ Pittsburgh PA 15213 USA Columbia Univ New York NY USA
We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) [27] for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense sema... 详细信息
来源: 评论
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neu...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Ma, Ruichen Qiao, Guanchao Liu, Yian Meng, Liwei Ning, Ning Liu, Yang Hu, Shaogang Univ Elect Sci & Technol China Chengdu Peoples R China
Binary neural networks utilize 1-bit quantized weights and activations to reduce both the model's storage demands and computational burden. However, advanced binary architectures still incorporate millions of inef... 详细信息
来源: 评论
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
From Correspondences to Pose: Non-minimal Certifiably Optima...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Tirado-Garin, Javier Civera, Javier Univ Zaragoza I3A Zaragoza Spain
Estimating the relative camera pose from n >= 5 correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix ... 详细信息
来源: 评论
Unlocking Pre-trained Image Backbones for Semantic Image Synthesis
Unlocking Pre-trained Image Backbones for Semantic Image Syn...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Berrada, Tariq Verbeek, Jakob Couprie, Camille Alahari, Karteek Meta FAIR Menlo Pk CA 94025 USA Univ Grenoble Alpes LJK Grenoble INP InriaCNRS Grenoble France
Semantic image synthesis, i.e., generating images from user-provided semantic label maps, is an important conditional image generation task as it allows to control both the content as well as the spatial layout of gen... 详细信息
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CPLIP: Zero-Shot Learning for Histopathology with Comprehensive vision-Language Alignment
CPLIP: Zero-Shot Learning for Histopathology with Comprehens...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Javed, Sajid Mahmood, Arif Ganapathil, Iyyakutti Iyappan Dharej, Fayaz Ali Werghil, Naoufel Bennamoun, Mohammed Khalifa Univ Sci & Technol Dept Comp Sci Abu Dhabi U Arab Emirates Khalifa Univ Sci & Technol C2PS Abu Dhabi U Arab Emirates Informat Technol Univ Punjab Lahore Pakistan Univ Western Australia Perth WA Australia
This paper proposes Comprehensive Pathology Language Image Pre-training (CPLIP), a new unsupervised technique designed to enhance the alignment of images and text in histopathology for tasks such as classification and... 详细信息
来源: 评论
Situational Awareness Matters in 3D vision Language Reasoning
Situational Awareness Matters in 3D Vision Language Reasonin...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Man, Yunze Gui, Liang-Yan Wang, Yu-Xiong Univ Illinois Urbana IL 61801 USA
Being able to carry out complicated vision language reasoning tasks in 3D space represents a significant milestone in developing household robots and human-centered embodied AI. In this work, we demonstrate that a cri... 详细信息
来源: 评论
ELSA: Exploiting Layer-wise N:M Sparsity for vision Transformer Acceleration
ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transfor...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Huang, Ning-Chi Chang, Chi-Chih Lin, Wei-Cheng Taka, Endri Marculescu, Diana Wu, Kai-Chiang Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan Univ Texas Austin Austin TX USA
N:M sparsity is an emerging model compression method supported by more and more accelerators to speed up sparse matrix multiplication in deep neural networks. Most existing N:M sparsity methods compress neural network... 详细信息
来源: 评论