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19982026
most citedConvergence of Edge Computing and Deep Learning: A Comprehensive Survey

1.5k citations

Showing 2023 · cs.CVShow all

13 papers · 2 filters

cs.CV2023★ 65 cited

Uni-paint: A Unified Framework for Multimodal Image Inpainting with Pretrained Diffusion Model

Shiyuan Yang, Xiaodong Chen, Jing Liao

Recently, text-to-image denoising diffusion probabilistic models (DDPMs) have demonstrated impressive image generation capabilities and have also been successfully applied to image…

cs.CV2023

T2IW: Joint Text to Image & Watermark Generation

An-An Liu, Guokai Zhang, Yuting Su +3

Recent developments in text-conditioned image generative models have revolutionized the production of realistic results. Unfortunately, this has also led to an increase in privacy…

cs.CV2023★ 30 cited

Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer

Zhijin Ge, Fanhua Shang, Hongying Liu +4

Deep neural networks are vulnerable to adversarial examples crafted by applying human-imperceptible perturbations on clean inputs. Although many attack methods can achieve high suc…

cs.CV2023★ 2 cited

Surface Geometry Processing: An Efficient Normal-based Detail Representation

Wuyuan Xie, Miaohui Wang, Di Lin +2

With the rapid development of high-resolution 3D vision applications, the traditional way of manipulating surface detail requires considerable memory and computing time. To address…

cs.CV2023

CVSformer: Cross-View Synthesis Transformer for Semantic Scene Completion

Haotian Dong, Enhui Ma, Lubo Wang +7

Semantic scene completion (SSC) requires an accurate understanding of the geometric and semantic relationships between the objects in the 3D scene for reasoning the occluded object…

cs.CV2023★ 15 cited

Hierarchical Matching and Reasoning for Multi-Query Image Retrieval

Zhong Ji, Zhihao Li, Yan Zhang +3

As a promising field, Multi-Query Image Retrieval (MQIR) aims at searching for the semantically relevant image given multiple region-specific text queries. Existing works mainly fo…

cs.CV2023★ 5 cited

Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation

Likang Wu, Zhi Li, Hongke Zhao +5

Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.…

cs.CV2023★ 63 cited

Semantic Invariant Multi-view Clustering with Fully Incomplete Information

Pengxin Zeng, Mouxing Yang, Yiding Lu +3

Robust multi-view learning with incomplete information has received significant attention due to issues such as incomplete correspondences and incomplete instances that commonly af…

cs.CV2023★ 10 cited

Transformer-based stereo-aware 3D object detection from binocular images

Hanqing Sun, Yanwei Pang, Jiale Cao +2

Transformers have shown promising progress in various visual object detection tasks, including monocular 2D/3D detection and surround-view 3D detection. More importantly, the atten…

cs.CV2023★ 62 cited

Unified Multi-Modal Image Synthesis for Missing Modality Imputation

Yue Zhang, Chengtao Peng, Qiuli Wang +3

Multi-modal medical images provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scanning time, image corruption a…

cs.CV2023★ 71 cited

HybridMIM: A Hybrid Masked Image Modeling Framework for 3D Medical Image Segmentation

Zhaohu Xing, Lei Zhu, Lequan Yu +2

Masked image modeling (MIM) with transformer backbones has recently been exploited as a powerful self-supervised pre-training technique. The existing MIM methods adopt the strategy…

cs.CV2023★ 28 cited

Deep Intra-Image Contrastive Learning for Weakly Supervised One-Step Person Search

Jiabei Wang, Yanwei Pang, Jiale Cao +3

Weakly supervised person search aims to perform joint pedestrian detection and re-identification (re-id) with only person bounding-box annotations. Recently, the idea of contrastiv…

cs.CV2023★ 3 cited

Face Inverse Rendering via Hierarchical Decoupling

Meng Wang, Xiaojie Guo, Wenjing Dai +1

Previous face inverse rendering methods often require synthetic data with ground truth and/or professional equipment like a lighting stage. However, a model trained on synthetic da…