Search Results for author:
Found 9 papers, 3 papers with code
MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation
To address the target scale variation issue in interactive segmentation, a novel multi-scale token adaptation algorithm is proposed.
Ranked #1 on
Interactive Segmentation
on DAVIS-585
Contextual Modeling for 3D Dense Captioning on Point Clouds
With such global and local contextual modeling strategies, our proposed model can effectively characterize the object representations and contextual information and thereby generate comprehensive and detailed descriptions of the located objects.
Deep Learning Eliminates Massive Dust Storms from Images of Tianwen-1
Inspired by the haze formation process on Earth, we formulate a similar visual degradation process on clean images and synthesize dusty images sharing a similar feature distribution with realistic dusty images.
Complementary Feature Enhanced Network with Vision Transformer for Image Dehazing
In this paper, firstly, we propose a new complementary feature enhanced framework, in which the complementary features are learned by several complementary subtasks and then together serve to boost the performance of the primary task.
Ranked #1 on
Image Dehazing
on NH-HAZE
Echoes in Unidirectionally Rotating Molecules
Abstract We report the experimental observation of molecular unidirectional rotation (UDR) echoes, and analyze their origin and behavior both classically and quantum mechanically.
Optics
Image Quality Assessment for Omnidirectional Cross-reference Stitching
Along with the development of virtual reality (VR), omnidirectional images play an important role in producing multimedia content with immersive experience.
Frequency-resolved photon-electronic spectroscopy for excited state population detection
With the advantage of separation, we provide a scheme to reconstruct populations on different excited states after the first pulse.
Atomic Physics Optics
Visual Attention on the Sun: What Do Existing Models Actually Predict?
Visual attention prediction is a classic problem that seems to be well addressed in the deep learning era.
Image Quality Assessment Guided Deep Neural Networks Training
For many computer vision problems, the deep neural networks are trained and validated based on the assumption that the input images are pristine (i. e., artifact-free).
