2.4k citations · 8k across the 63 of their papers we have counts for
12 papers · 1 filter
CamoFormer: Masked Separable Attention for Camouflaged Object Detection
Bowen Yin, Xuying Zhang, Qibin Hou +3
How to identify and segment camouflaged objects from the background is challenging. Inspired by the multi-head self-attention in Transformers, we present a simple masked separable…
Source-free Depth for Object Pop-out
Zongwei Wu, Danda Pani Paudel, Deng-Ping Fan +5
Depth cues are known to be useful for visual perception. However, direct measurement of depth is often impracticable. Fortunately, though, modern learning-based methods offer promi…
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…
OSFormer: One-Stage Camouflaged Instance Segmentation with Transformers
Jialun Pei, Tianyang Cheng, Deng-Ping Fan +3
We present OSFormer, the first one-stage transformer framework for camouflaged instance segmentation (CIS). OSFormer is based on two key designs. First, we design a location-sensin…
GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector
Peng Zheng, Huazhu Fu, Deng-Ping Fan +5
In this paper, we present a novel end-to-end group collaborative learning network, termed GCoNet+, which can effectively and efficiently (250 fps) identify co-salient objects in na…
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…
Towards Deeper Understanding of Camouflaged Object Detection
Yunqiu Lv, Jing Zhang, Yuchao Dai +3
Preys in the wild evolve to be camouflaged to avoid being recognized by predators. In this way, camouflage acts as a key defence mechanism across species that is critical to surviv…
Implicit Motion Handling for Video Camouflaged Object Detection
Xuelian Cheng, Huan Xiong, Deng-Ping Fan +4
We propose a new video camouflaged object detection (VCOD) framework that can exploit both short-term dynamics and long-term temporal consistency to detect camouflaged objects from…
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…
Practical Blind Image Denoising via Swin-Conv-UNet and Data Synthesis
Kai Zhang, Yawei Li, Jingyun Liang +6
While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, su…
High-resolution Iterative Feedback Network for Camouflaged Object Detection
Xiaobin Hu, Shuo Wang, Xuebin Qin +5
Spotting camouflaged objects that are visually assimilated into the background is tricky for both object detection algorithms and humans who are usually confused or cheated by the…
Highly Accurate Dichotomous Image Segmentation
Xuebin Qin, Hang Dai, Xiaobin Hu +3
We present a systematic study on a new task called dichotomous image segmentation (DIS) , which aims to segment highly accurate objects from natural images. To this end, we collect…