activity
20192021
most citedExploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

107 citations · 112 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Learning Visual Affordance Grounding from Demonstration Videos

Hongchen Luo, Wei Zhai, Jing Zhang +2

Visual affordance grounding aims to segment all possible interaction regions between people and objects from an image/video, which is beneficial for many applications, such as robo…

cs.CV2021

One-Shot Object Affordance Detection in the Wild

Wei Zhai, Hongchen Luo, Jing Zhang +2

Affordance detection refers to identifying the potential action possibilities of objects in an image, which is a crucial ability for robot perception and manipulation. To empower r…

cs.CV2021★ 107 cited

Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Wen Wang, Yang Cao, Jing Zhang +4

Detection transformers have recently shown promising object detection results and attracted increasing attention. However, how to develop effective domain adaptation techniques to…

cs.CV2021

One-Shot Affordance Detection

Hongchen Luo, Wei Zhai, Jing Zhang +2

Affordance detection refers to identifying the potential action possibilities of objects in an image, which is an important ability for robot perception and manipulation. To empowe…

cs.CV2020★ 1 cited

Nighttime Dehazing with a Synthetic Benchmark

Jing Zhang, Yang Cao, Zheng-Jun Zha +1

Increasing the visibility of nighttime hazy images is challenging because of uneven illumination from active artificial light sources and haze absorbing/scattering. The absence of…

cs.LG2019★ 4 cited

Deep Time-Frequency Representation and Progressive Decision Fusion for ECG Classification

Jing Zhang, Jing Tian, Yang Cao +2

Early recognition of abnormal rhythms in ECG signals is crucial for monitoring and diagnosing patients' cardiac conditions, increasing the success rate of the treatment. Classifyin…