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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12857 条 记 录,以下是311-320 订阅
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Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Project...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wimmer, Thomas Wonka, Peter Ovsjanikov, Maks Ecole Polytech LIX Palaiseau France Tech Univ Munich Munich Germany KAUST Thuwal Saudi Arabia
With the immense growth of dataset sizes and computing resources in recent years, so-called foundation models have become popular in NLP and vision tasks. In this work, we propose to explore foundation models for the ... 详细信息
来源: 评论
Gradient Reweighting: Towards Imbalanced Class-Incremental Learning
Gradient Reweighting: Towards Imbalanced Class-Incremental L...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: He, Jiangpeng Purdue Univ Elmore Family Sch Elect & Comp Engn W Lafayette IN 47907 USA
Class-Incremental Learning (CIL) trains a model to continually recognize new classes from non-stationary data while retaining learned knowledge. A major challenge of CIL arises when applying to real-world data charact... 详细信息
来源: 评论
Sieve: Multimodal Dataset Pruning Using Image Captioning Models
Sieve: Multimodal Dataset Pruning Using Image Captioning Mod...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Mahmouc, Anas Elhoushi, Mostafa Abbass, Amro Yang, Yu Ardalani, Newsha Leather, Hugh Morcos, Art S. Meta FAIR Menlo Pk CA 94025 USA Univ Toronto Toronto ON Canada UC Los Angeles Los Angeles CA USA DatologyAI Redwood City CA USA
vision-Language Models (VLMs) are pretrained on large, diverse, and noisy web-crawled datasets. This underscores the critical need for dataset pruning, as the quality of these datasets is strongly correlated with the ... 详细信息
来源: 评论
Active Prompt Learning in vision Language Models
Active Prompt Learning in Vision Language Models
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Bang, Jihwan Ahn, Sumyeong Lee, Jae-Gil Korea Adv Inst Sci & Technol Daejeon South Korea Michigan State Univ E Lansing MI USA
Pre-trained vision Language Models (VLMs) have demonstrated notable progress in various zero-shot tasks, such as classification and retrieval. Despite their performance, because improving performance on new tasks requ...
来源: 评论
Multiscale vision Transformers meet Bipartite Matching for efficient single-stage Action Localization
Multiscale Vision Transformers meet Bipartite Matching for e...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Ntinou, Ioanna Sanchez, Enrique Tzimiropoulos, Georgios Queen Mary Univ London London England Samsung AI Ctr Cambridge Cambridge England
Action Localization is a challenging problem that combines detection and recognition tasks, which are often addressed separately. State-of-the-art methods rely on off-the-shelf bounding box detections pre-computed at ... 详细信息
来源: 评论
LowRankOcc: Tensor Decomposition and Low-Rank Recovery for vision-based 3D Semantic Occupancy Prediction
LowRankOcc: Tensor Decomposition and Low-Rank Recovery for V...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zhao, Linqing Xu, Xiuwei Wang, Ziwei Zhang, Yunpeng Zhang, Borui Zheng, Wenzhao Du, Dalong Zhou, Jie Lu, Jiwen Tsinghua Univ Dept Automat Beijing Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China PhiGent Robot Beijing Peoples R China
In this paper, we present a tensor decomposition and low-rank recovery approach (LowRankOcc) for vision-based 3D semantic occupancy prediction. Conventional methods model outdoor scenes with fine-grained 3D grids, but... 详细信息
来源: 评论
USE: Universal Segment Embeddings for Open-Vocabulary Image Segmentation
USE: Universal Segment Embeddings for Open-Vocabulary Image ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wang, Xiaoqi He, Wenbin Xuan, Xiwei Sebastian, Clint Ono, Jorge Piazentin Li, Xin Behpour, Sima Thang Doan Gou, Liang Shen, Han-Wei Ren, Liu Bosch Res North Amer Oak Brook Terrace IL 60181 USA Bosch Ctr Artificial Intelligence Baden Baden Germany Ohio State Univ Columbus OH 43210 USA Univ Calif Davis Davis CA 95616 USA
The open-vocabulary image segmentation task involves partitioning images into semantically meaningful segments and classifying them with flexible text-defined categories. The recent vision-based foundation models such... 详细信息
来源: 评论
Collaborating Foundation Models for Domain Generalized Semantic Segmentation
Collaborating Foundation Models for Domain Generalized Seman...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Benigmim, Yasser Roy, Subhankar Essid, Slim Kalogeiton, Vicky Lathuiliere, Stephane Inst Polytech Paris Telecom Paris LTCI Palaiseau France Inst Polytech Paris CNRS Ecole Polytech LIX Palaiseau France Univ Aberdeen Aberdeen Scotland
Domain Generalized Semantic Segmentation (DGSS) deals with training a model on a labeled source domain with the aim of generalizing to unseen domains during inference. Existing DGSS methods typically effectuate robust... 详细信息
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Boosting Adversarial Transferability by Block Shuffle and Rotation
Boosting Adversarial Transferability by Block Shuffle and Ro...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Wang, Kunyu He, Xuanran Wang, Wenxuan Wang, Xiaosen Chinese Univ Hong Kong Hong Kong Peoples R China Nanyang Technol Univ Singapore Singapore Huawei Singular Secur Lab Beijing Peoples R China
Adversarial examples mislead deep neural networks with imperceptible perturbations and have brought significant threats to deep learning. An important aspect is their transferability, which refers to their ability to ... 详细信息
来源: 评论
Edit One for All: Interactive Batch Image Editing
Edit One for All: Interactive Batch Image Editing
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Thao Nguyen Ojha, Utkarsh Li, Yuheng Liu, Haotian Lee, Yong Jae Univ Wisconsin Madison Madison WI 53707 USA
In recent years, image editing has advanced remarkably. With increased human control, it is now possible to edit an image in a plethora of ways;from specifying in text what we want to change, to straight up dragging t... 详细信息
来源: 评论