107 citations · 187 across the 11 of their papers we have counts for
12 papers
Leveraging Failed Samples: A Few-Shot and Training-Free Framework for Generalized Deepfake Detection
Shibo Yao, Renshuai Tao, Xiaolong Zheng +2
Recent deepfake detection studies often treat unseen sample detection as a ``zero-shot" task, training on images generated by known models but generalizing to unknown ones. A key r…
Leveraging Unlabeled Data from Unknown Sources via Dual-Path Guidance for Deepfake Face Detection
Zhiqiang Yang, Renshuai Tao, Chunjie Zhang +3
Existing deepfake detection methods heavily rely on static labeled datasets. However, with the proliferation of generative models, real-world scenarios are flooded with massive amo…
PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning
Man Liu, Huihui Bai, Feng Li +5
Generalized zero-shot learning (GZSL) endeavors to identify the unseen categories using knowledge from the seen domain, necessitating the intrinsic interactions between the visual…
Attend and Enrich: Enhanced Visual Prompt for Zero-Shot Learning
Man Liu, Huihui Bai, Feng Li +4
Zero-shot learning (ZSL) endeavors to transfer knowledge from seen categories to recognize unseen categories, which mostly relies on the semantic-visual interactions between image…
CTP: Towards Vision-Language Continual Pretraining via Compatible Momentum Contrast and Topology Preservation
Hongguang Zhu, Yunchao Wei, Xiaodan Liang +2
Vision-Language Pretraining (VLP) has shown impressive results on diverse downstream tasks by offline training on large-scale datasets. Regarding the growing nature of real-world d…
You Can Mask More For Extremely Low-Bitrate Image Compression
Anqi Li, Feng Li, Jiaxin Han +6
Learned image compression (LIC) methods have experienced significant progress during recent years. However, these methods are primarily dedicated to optimizing the rate-distortion…
Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learning
Man Liu, Feng Li, Chunjie Zhang +3
Generalized Zero-Shot Learning (GZSL) identifies unseen categories by knowledge transferred from the seen domain, relying on the intrinsic interactions between visual and semantic…
Learning Detail-Structure Alternative Optimization for Blind Super-Resolution
Feng Li, Yixuan Wu, Huihui Bai +3
Existing convolutional neural networks (CNN) based image super-resolution (SR) methods have achieved impressive performance on bicubic kernel, which is not valid to handle unknown…
Towards Fast and Accurate Real-World Depth Super-Resolution: Benchmark Dataset and Baseline
Lingzhi He, Hongguang Zhu, Feng Li +6
Depth maps obtained by commercial depth sensors are always in low-resolution, making it difficult to be used in various computer vision tasks. Thus, depth map super-resolution (SR)…
Progressively Complementary Network for Fisheye Image Rectification Using Appearance Flow
Shangrong Yang, Chunyu Lin, Kang Liao +2
Distortion rectification is often required for fisheye images. The generation-based method is one mainstream solution due to its label-free property, but its naive skip-connection…
A Parallel Down-Up Fusion Network for Salient Object Detection in Optical Remote Sensing Images
Chongyi Li, Runmin Cong, Chunle Guo +4
The diverse spatial resolutions, various object types, scales and orientations, and cluttered backgrounds in optical remote sensing images (RSIs) challenge the current salient obje…
Body Joint guided 3D Deep Convolutional Descriptors for Action Recognition
Congqi Cao, Yifan Zhang, Chunjie Zhang +1
Three dimensional convolutional neural networks (3D CNNs) have been established as a powerful tool to simultaneously learn features from both spatial and temporal dimensions, which…