On the challenges and perspectives of foundation models for medical image analysis
This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …
pretrained models, ie, foundation models, which promise to significantly improve the …
Foundational models defining a new era in vision: A survey and outlook
Vision systems to see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …
fundamental to understanding our world. The complex relations between objects and their …
Segment anything is not always perfect: An investigation of sam on different real-world applications
Abstract Recently, Meta AI Research approaches a general, promptable segment anything
model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B) …
model (SAM) pre-trained on an unprecedentedly large segmentation dataset (SA-1B) …
Polyp-pvt: Polyp segmentation with pyramid vision transformers
Most polyp segmentation methods use CNNs as their backbone, leading to two key issues
when exchanging information between the encoder and decoder: 1) taking into account the …
when exchanging information between the encoder and decoder: 1) taking into account the …
Camouflaged object detection via context-aware cross-level fusion
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 …
natural scenes. Accurate COD suffers from a number of challenges associated with low …
Deep gradient learning for efficient camouflaged object detection
This paper introduces deep gradient network (DGNet), a novel deep framework that exploits
object gradient supervision for camouflaged object detection (COD). It decouples the task …
object gradient supervision for camouflaged object detection (COD). It decouples the task …
See more and know more: Zero-shot point cloud segmentation via multi-modal visual data
Zero-shot point cloud segmentation aims to make deep models capable of recognizing
novel objects in point cloud that are unseen in the training phase. Recent trends favor the …
novel objects in point cloud that are unseen in the training phase. Recent trends favor the …
Tall: Thumbnail layout for deepfake video detection
The growing threats of deepfakes to society and cybersecurity have raised enormous public
concerns, and increasing efforts have been devoted to this critical topic of deepfake video …
concerns, and increasing efforts have been devoted to this critical topic of deepfake video …
Advances in deep concealed scene understanding
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 …
objects exhibiting camouflage. The current boom in terms of techniques and applications …
Uniseg: A unified multi-modal lidar segmentation network and the openpcseg codebase
Abstract Point-, voxel-, and range-views are three representative forms of point clouds. All of
them have accurate 3D measurements but lack color and texture information. RGB images …
them have accurate 3D measurements but lack color and texture information. RGB images …