122 citations · 372 across the 33 of their papers we have counts for
34 papers
SceneReGen: Generative Reconstruction of 3D Scenes from a Single Image
Zefan Tian, Yuteng Ye, Yiheng Zhang +5
Single-image 3D scene reconstruction must complete partially observed objects and place them coherently in a shared observation-aligned scene frame. Object-level generative priors…
Temporal-Emerged Prompting for Segment Anything in Multiframe Infrared Small Target Detection
Yinghui Xing, Donghao Chu, Shizhou Zhang +1
Accurately localizing and segmenting small targets in low signal-to-noise ratio (SNR) infrared sequences remains a challenging task. Since targets are often indistinguishable from…
Better Matching, Less Forgetting: A Quality-Guided Matcher for Transformer-based Incremental Object Detection
Qirui Wu, Shizhou Zhang, De Cheng +4
Incremental Object Detection (IOD) aims to continuously learn new object classes without forgetting previously learned ones. A persistent challenge is catastrophic forgetting, prim…
Knowing the Unknown: Interpretable Open-World Object Detection via Concept Decomposition Model
Xueqiang Lv, Shizhou Zhang, Yinghui Xing +3
Open-world object detection (OWOD) requires incrementally detecting known categories while reliably identifying unknown objects. Existing methods primarily focus on improving unkno…
Attention Retention for Continual Learning with Vision Transformers
Yue Lu, Xiangyu Zhou, Shizhou Zhang +3
Continual learning (CL) empowers AI systems to progressively acquire knowledge from non-stationary data streams. However, catastrophic forgetting remains a critical challenge. In t…
YOLO-IOD: Towards Real Time Incremental Object Detection
Shizhou Zhang, Xueqiang Lv, Yinghui Xing +4
Current methods for incremental object detection (IOD) primarily rely on Faster R-CNN or DETR series detectors; however, these approaches do not accommodate the real-time YOLO dete…
DuGI-MAE: Improving Infrared Mask Autoencoders via Dual-Domain Guidance
Yinghui Xing, Xiaoting Su, Shizhou Zhang +2
Infrared imaging plays a critical role in low-light and adverse weather conditions. However, due to the distinct characteristics of infrared images, existing foundation models such…
On Modality Incomplete Infrared-Visible Object Detection: An Architecture Compatibility Perspective
Shuo Yang, Yinghui Xing, Shizhou Zhang +1
Infrared and visible object detection (IVOD) is essential for numerous around-the-clock applications. Despite notable advancements, current IVOD models exhibit notable performance…
Multi-level Collaborative Distillation Meets Global Workspace Model: A Unified Framework for OCIL
Shibin Su, Guoqiang Liang, De Cheng +2
Online Class-Incremental Learning (OCIL) enables models to learn continuously from non-i.i.d. data streams. Since samples of the data streams can be seen only once, it is more suit…
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation
Lingyan Ran, Yali Li, Tao Zhuo +2
In semi-supervised semantic segmentation (SSSS), data augmentation plays a crucial role in the weak-to-strong consistency regularization framework, as it enhances diversity and imp…
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng +4
Catastrophic forgetting is a critical chanllenge for incremental object detection (IOD). Most existing methods treat the detector monolithically, relying on instance replay or know…
ComprehendEdit: A Comprehensive Dataset and Evaluation Framework for Multimodal Knowledge Editing
Yaohui Ma, Xiaopeng Hong, Shizhou Zhang +4
Large multimodal language models (MLLMs) have revolutionized natural language processing and visual understanding, but often contain outdated or inaccurate information. Current mul…
Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning
De Cheng, Yue Lu, Lingfeng He +4
Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowledge. Recently, State Space Mode…
AdaSemiCD: An Adaptive Semi-Supervised Change Detection Method Based on Pseudo-Label Evaluation
Ran Lingyan, Wen Dongcheng, Zhuo Tao +3
Change Detection (CD) is an essential field in remote sensing, with a primary focus on identifying areas of change in bi-temporal image pairs captured at varying intervals of the s…
Frequency-Guided Spatial Adaptation for Camouflaged Object Detection
Shizhou Zhang, Dexuan Kong, Yinghui Xing +5
Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that e…
Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation Approach
Shizhou Zhang, Wenlong Luo, De Cheng +4
In this paper, we construct a large-scale benchmark dataset for Ground-to-Aerial Video-based person Re-Identification, named G2A-VReID, which comprises 185,907 images and 5,576 tra…
Visual Prompt Tuning in Null Space for Continual Learning
Yue Lu, Shizhou Zhang, De Cheng +4
Existing prompt-tuning methods have demonstrated impressive performances in continual learning (CL), by selecting and updating relevant prompts in the vision-transformer models. On…
Dual-Modal Prompting for Sketch-Based Image Retrieval
Liying Gao, Bingliang Jiao, Peng Wang +3
Sketch-based image retrieval (SBIR) associates hand-drawn sketches with their corresponding realistic images. In this study, we aim to tackle two major challenges of this task simu…
DMAT: A Dynamic Mask-Aware Transformer for Human De-occlusion
Guoqiang Liang, Jiahao Hu, Qingyue Wang +1
Human de-occlusion, which aims to infer the appearance of invisible human parts from an occluded image, has great value in many human-related tasks, such as person re-id, and inten…
CrossDiff: Exploring Self-Supervised Representation of Pansharpening via Cross-Predictive Diffusion Model
Yinghui Xing, Litao Qu, Shizhou Zhang +2
Fusion of a panchromatic (PAN) image and corresponding multispectral (MS) image is also known as pansharpening, which aims to combine abundant spatial details of PAN and spectral i…
Zero-Shot Object Goal Visual Navigation With Class-Independent Relationship Network
Xinting Li, Shiguang Zhang, Yue LU +2
This paper investigates the zero-shot object goal visual navigation problem. In the object goal visual navigation task, the agent needs to locate navigation targets from its egocen…
Ground-to-Aerial Person Search: Benchmark Dataset and Approach
Shizhou Zhang, Qingchun Yang, De Cheng +4
In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31,770 images of 260,559 annotated bounding boxes for 2,644 identit…
Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection
Yinghui Xing, Dexuan Kong, Shizhou Zhang +4
Camouflaged object detection (COD), aiming to segment camouflaged objects which exhibit similar patterns with the background, is a challenging task. Most existing works are dedicat…
Efficient Bilateral Cross-Modality Cluster Matching for Unsupervised Visible-Infrared Person ReID
De Cheng, Lingfeng He, Nannan Wang +3
Unsupervised visible-infrared person re-identification (USL-VI-ReID) aims to match pedestrian images of the same identity from different modalities without annotations. Existing wo…