7 citations · 26 across the 13 of their papers we have counts for
15 papers
RPCANet++: Deep Interpretable Robust PCA for Sparse Object Segmentation
Fengyi Wu, Yimian Dai, Tianfang Zhang +4
Robust principal component analysis (RPCA) decomposes an observation matrix into low-rank background and sparse object components. This capability has enabled its application in ta…
DISTA-Net: Dynamic Closely-Spaced Infrared Small Target Unmixing
Shengdong Han, Shangdong Yang, Xin Zhang +5
Resolving closely-spaced small targets in dense clusters presents a significant challenge in infrared imaging, as the overlapping signals hinder precise determination of their quan…
AuxDet: Auxiliary Metadata Matters for Omni-Domain Infrared Small Target Detection
Yangting Shi, Yinfei Zhu, Renjie He +4
Omni-domain infrared small target detection (Omni-IRSTD) poses formidable challenges, as a single model must seamlessly adapt to diverse imaging systems, varying resolutions, and m…
Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing
Taihang Hu, Linxuan Li, Kai Wang +3
Text-to-image generation has seen groundbreaking advancements with diffusion models, enabling high-fidelity synthesis and precise image editing through cross-attention manipulation…
InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer +6
Diffusion priors have been used for blind face restoration (BFR) by fine-tuning diffusion models (DMs) on restoration datasets to recover low-quality images. However, the naive app…
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection
Xinbin Yuan, Zhaohui Zheng, Yuxuan Li +5
While witnessed with rapid development, remote sensing object detection remains challenging for detecting high aspect ratio objects. This paper shows that large strip convolutions…
One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
Tao Liu, Kai Wang, Senmao Li +6
Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements f…
RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark
Xin Zhang, Xue Yang, Yuxuan Li +3
Rotated object detection has made significant progress in the optical remote sensing. However, advancements in the Synthetic Aperture Radar (SAR) field are laggard behind, primaril…
SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection
Yuxuan Li, Xiang Li, Yunheng Li +5
With the rapid advancement of remote sensing technology, high-resolution multi-modal imagery is now more widely accessible. Conventional Object detection models are trained on a si…
Advancing Textual Prompt Learning with Anchored Attributes
Zheng Li, Yibing Song, Ming-Ming Cheng +2
Textual-based prompt learning methods primarily employ multiple learnable soft prompts and hard class tokens in a cascading manner as text inputs, aiming to align image and text (c…
Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis
Taihang Hu, Linxuan Li, Joost van de Weijer +6
Although text-to-image (T2I) models exhibit remarkable generation capabilities, they frequently fail to accurately bind semantically related objects or attributes in the input prom…
From Words to Worth: Newborn Article Impact Prediction with LLM
Penghai Zhao, Qinghua Xing, Kairan Dou +5
As the academic landscape expands, the challenge of efficiently identifying impactful newly published articles grows increasingly vital. This paper introduces a promising approach,…
LSKNet: A Foundation Lightweight Backbone for Remote Sensing
Yuxuan Li, Xiang Li, Yimian Dai +5
Remote sensing images pose distinct challenges for downstream tasks due to their inherent complexity. While a considerable amount of research has been dedicated to remote sensing c…
A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence
Penghai Zhao, Xin Zhang, Jiayue Cao +3
The rapid growth of research in Pattern Analysis and Machine Intelligence (PAMI) has rendered literature reviews essential for consolidating and interpreting knowledge across its m…
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference
Senmao Li, Taihang Hu, Joost van de Weijer +7
One of the main drawback of diffusion models is the slow inference time for image generation. Among the most successful approaches to addressing this problem are distillation metho…