Search Results for author:
Found 12 papers, 3 papers with code
Incorporating Depth into both CNN and CRF for Indoor Semantic Segmentation
To improve segmentation performance, a novel neural network architecture (termed DFCN-DCRF) is proposed, which combines an RGB-D fully convolutional neural network (DFCN) with a depth-sensitive fully-connected conditional random field (DCRF).
Weighted Low-rank Tensor Recovery for Hyperspectral Image Restoration
To overcome these limitations, in this work, we propose a unified low-rank tensor recovery model for comprehensive HSI restoration tasks, in which non-local similarity between spectral-spatial cubic and spectral correlation are simultaneously captured by 3-order tensors.
Ranked #12 on
Hyperspectral Image Denoising
on ICVL-HSI-Gaussian50
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
Indoor semantic segmentation has always been a difficult task in computer vision.
Ranked #26 on
Semantic Segmentation
on SUN-RGBD
(using extra training data)
A Gegenbauer Neural Network with Regularized Weights Direct Determination for Classification
Single-hidden layer feed forward neural networks (SLFNs) are widely used in pattern classification problems, but a huge bottleneck encountered is the slow speed and poor performance of the traditional iterative gradient-based learning algorithms.
Learning Oriented Remote Sensing Object Detection via Naive Geometric Computing
Detecting oriented objects along with estimating their rotation information is one crucial step for analyzing remote sensing images.
Effective Actor-centric Human-object Interaction Detection
Moreover, we also use an actor branch to get interaction prediction of the actor and propose a novel composition strategy based on center-point indexing to generate the final HOI prediction.
Category-Aware Transformer Network for Better Human-Object Interaction Detection
Specifically, the Object Query would be initialized via category priors represented by an external object detection model to yield better performance.
High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation
We implement the IAT in a mathematical invertible manner on a single rate Invertible Neural Network (INN) based model and the quality level (QLevel) would be fed into the IAT to generate scaling and bias tensors.
Base Placement Optimization for Coverage Mobile Manipulation Tasks
More tricky is that some task constraints are flexible and non-deterministic.
UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity
In this work, we propose UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity.
A Grammatical Compositional Model for Video Action Detection
Analysis of human actions in videos demands understanding complex human dynamics, as well as the interaction between actors and context.
Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy
This survey comprehensively examines the emerging field of AIGC-based Brain-conditional Multimodal Synthesis, termed AIGC-Brain, to delineate the current landscape and future directions.
