2.4k citations · 8k across the 63 of their papers we have counts for
12 papers · 1 filter
Edge-aware Feature Aggregation Network for Polyp Segmentation
Tao Zhou, Yizhe Zhang, Geng Chen +3
Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer (CRC) in clinical practice. However, due to scale variation and blurry polyp boundar…
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…
OnUVS: Online Feature Decoupling Framework for High-Fidelity Ultrasound Video Synthesis
Han Zhou, Dong Ni, Ao Chang +10
Ultrasound (US) imaging is indispensable in clinical practice. To diagnose certain diseases, sonographers must observe corresponding dynamic anatomic structures to gather comprehen…
CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance Segmentation
Jialun Pei, Tao Jiang, He Tang +4
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet. Our method simultaneously cali…
Instructive Feature Enhancement for Dichotomous Medical Image Segmentation
Lian Liu, Han Zhou, Jiongquan Chen +5
Deep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance.…
Referring Camouflaged Object Detection
Xuying Zhang, Bowen Yin, Zheng Lin +3
We consider the problem of referring camouflaged object detection (Ref-COD), a new task that aims to segment specified camouflaged objects based on a small set of referring images…
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
WinDB: HMD-free and Distortion-free Panoptic Video Fixation Learning
Guotao Wang, Chenglizhao Chen, Aimin Hao +2
To date, the widely adopted way to perform fixation collection in panoptic video is based on a head-mounted display (HMD), where users' fixations are collected while wearing an HMD…
CamDiff: Camouflage Image Augmentation via Diffusion Model
Xue-Jing Luo, Shuo Wang, Zongwei Wu +4
The burgeoning field of camouflaged object detection (COD) seeks to identify objects that blend into their surroundings. Despite the impressive performance of recent models, we hav…
RGB-D Indiscernible Object Counting in Underwater Scenes
Guolei Sun, Xiaogang Cheng, Zhaochong An +5
Recently, indiscernible/camouflaged scene understanding has attracted lots of research attention in the vision community. We further advance the frontier of this field by systemati…
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…