786 citations · 2.5k across the 30 of their papers we have counts for
31 papers
LawDIS: Language-Window-based Controllable Dichotomous Image Segmentation
Xinyu Yan, Meijun Sun, Ge-Peng Ji +3
We present LawDIS, a language-window-based controllable dichotomous image segmentation (DIS) framework that produces high-quality object masks. Our framework recasts DIS as an imag…
VideoExpert: Augmented LLM for Temporal-Sensitive Video Understanding
Henghao Zhao, Ge-Peng Ji, Rui Yan +2
The core challenge in video understanding lies in perceiving dynamic content changes over time. However, multimodal large language models struggle with temporal-sensitive video tas…
PraNet-V2: Dual-Supervised Reverse Attention for Medical Image Segmentation
Bo-Cheng Hu, Ge-Peng Ji, Dian Shao +1
Accurate medical image segmentation is essential for effective diagnosis and treatment. Previously, PraNet-V1 was proposed to enhance polyp segmentation by introducing a reverse at…
Patch is Enough: Naturalistic Adversarial Patch against Vision-Language Pre-training Models
Dehong Kong, Siyuan Liang, Xiaopeng Zhu +2
Visual language pre-training (VLP) models have demonstrated significant success across various domains, yet they remain vulnerable to adversarial attacks. Addressing these adversar…
Frontiers in Intelligent Colonoscopy
Ge-Peng Ji, Jingyi Liu, Peng Xu +4
Colonoscopy is currently one of the most sensitive screening methods for colorectal cancer. This study investigates the frontiers of intelligent colonoscopy techniques and their pr…
Effectiveness Assessment of Recent Large Vision-Language Models
Yao Jiang, Xinyu Yan, Ge-Peng Ji +5
The advent of large vision-language models (LVLMs) represents a remarkable advance in the quest for artificial general intelligence. However, the model's effectiveness in both spec…
Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detection
Xin Zhang, Tao Xiao, Gepeng Ji +3
Camouflage poses challenges in distinguishing a static target, whereas any movement of the target can break this disguise. Existing video camouflaged object detection (VCOD) approa…
MAST: Video Polyp Segmentation with a Mixture-Attention Siamese Transformer
Geng Chen, Junqing Yang, Xiaozhou Pu +5
Accurate segmentation of polyps from colonoscopy videos is of great significance to polyp treatment and early prevention of colorectal cancer. However, it is challenging due to the…
Large Model Based Referring Camouflaged Object Detection
Shupeng Cheng, Ge-Peng Ji, Pengda Qin +3
Referring camouflaged object detection (Ref-COD) is a recently-proposed problem aiming to segment out specified camouflaged objects matched with a textual or visual reference. This…
How Good is Google Bard's Visual Understanding? An Empirical Study on Open Challenges
Haotong Qin, Ge-Peng Ji, Salman Khan +3
Google's Bard has emerged as a formidable competitor to OpenAI's ChatGPT in the field of conversational AI. Notably, Bard has recently been updated to handle visual inputs alongsid…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
Rethinking Polyp Segmentation from an Out-of-Distribution Perspective
Ge-Peng Ji, Jing Zhang, Dylan Campbell +2
Unlike existing fully-supervised approaches, we rethink colorectal polyp segmentation from an out-of-distribution perspective with a simple but effective self-supervised learning a…
Advances in Deep Concealed Scene Understanding
Deng-Ping Fan, Ge-Peng Ji, Peng Xu +3
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive objects exhibiting camouflage. The current boom in terms of techniques and applications warran…
SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anything
Ge-Peng Ji, Deng-Ping Fan, Peng Xu +3
Segmenting anything is a ground-breaking step toward artificial general intelligence, and the Segment Anything Model (SAM) greatly fosters the foundation models for computer vision…
Masked Vision-Language Transformer in Fashion
Ge-Peng Ji, Mingcheng Zhuge, Dehong Gao +3
We present a masked vision-language transformer (MVLT) for fashion-specific multi-modal representation. Technically, we simply utilize vision transformer architecture for replacing…
Depth Quality-Inspired Feature Manipulation for Efficient RGB-D and Video Salient Object Detection
Wenbo Zhang, Keren Fu, Zhuo Wang +2
Recently CNN-based RGB-D salient object detection (SOD) has obtained significant improvement on detection accuracy. However, existing models often fail to perform well in terms of…
Camouflaged Object Detection via Context-aware Cross-level Fusion
Geng Chen, Si-Jie Liu, Yu-Jia Sun +3
Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes. Accurate COD suffers from a number of challenges associated with low boun…
Deep Gradient Learning for Efficient Camouflaged Object Detection
Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou +3
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branc…
Video Polyp Segmentation: A Deep Learning Perspective
Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou +4
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era. Over the years, developments in VPS are not moving forward with ease due to the la…
Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network
Ge-Peng Ji, Lei Zhu, Mingchen Zhuge +1
Camouflaged Object Detection (COD) aims to detect objects with similar patterns (e.g., texture, intensity, colour, etc) to their surroundings, and recently has attracted growing re…
Full-Duplex Strategy for Video Object Segmentation
Ge-Peng Ji, Deng-Ping Fan, Keren Fu +3
Previous video object segmentation approaches mainly focus on using simplex solutions between appearance and motion, limiting feature collaboration efficiency among and across thes…
Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection
Wenbo Zhang, Ge-Peng Ji, Zhuo Wang +2
RGB-D salient object detection (SOD) recently has attracted increasing research interest by benefiting conventional RGB SOD with extra depth information. However, existing RGB-D SO…
Progressively Normalized Self-Attention Network for Video Polyp Segmentation
Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan +4
Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features. However, due to their limited receptive fields, CNNs can n…
Camouflaged Object Segmentation with Distraction Mining
Haiyang Mei, Ge-Peng Ji, Ziqi Wei +3
Camouflaged object segmentation (COS) aims to identify objects that are "perfectly" assimilate into their surroundings, which has a wide range of valuable applications. The key cha…