activity
20192025
most citedPromoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection

16 citations · 21 across the 3 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2025

SAM3-I: Segment Anything with Instructions

Jingjing Li, Yue Feng, Yuchen Guo +10

Segment Anything Model 3 (SAM3) advances open-vocabulary segmentation through promptable concept segmentation, enabling users to segment all instances associated with a given conce…

cs.CV202216 cited

Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection

Wei Ji, Jingjing Li, Qi Bi +3

Growing interests in RGB-D salient object detection (RGB-D SOD) have been witnessed in recent years, owing partly to the popularity of depth sensors and the rapid progress of deep…

cs.CV20211 cited

CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search

Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Li Cheng +2

A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking resu…

cs.CV20204 cited

COMET: Context-Aware IoU-Guided Network for Small Object Tracking

Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan +2

We consider the problem of tracking an unknown small target from aerial videos of medium to high altitudes. This is a challenging problem, which is even more pronounced in unavoida…

cs.CV2019

Deep Learning for Visual Tracking: A Comprehensive Survey

Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan +1

Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. Given the ill-posed nature of the problem and its popularity in a broad r…