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Found 43 papers, 15 papers with code
PhraseClick: Toward Achieving Flexible Interactive Segmentation by Phrase and Click
We propose to employ phrase expressions as another interaction input to infer the attributes of target object.
GRES: Generalized Referring Expression Segmentation
Existing classic RES datasets and methods commonly support single-target expressions only, i. e., one expression refers to one target object.
Generalized Referring Expression Segmentation
Referring Expression
Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN
However, due to the quantization error and accumulating error, it often requires lots of time steps (high inference latency) to achieve high performance, which negates SNN's advantages.
Mask Attack Detection Using Vascular-weighted Motion-robust rPPG Signals
Detecting 3D mask attacks to a face recognition system is challenging.
Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentation
However, the generic attention mechanism in Transformer only uses the language input for attention weight calculation, which does not explicitly fuse language features in its output.
Prototype Adaption and Projection for Few- and Zero-shot 3D Point Cloud Semantic Segmentation
In this work, we address the challenging task of few-shot and zero-shot 3D point cloud semantic segmentation.
DANI-Net: Uncalibrated Photometric Stereo by Differentiable Shadow Handling, Anisotropic Reflectance Modeling, and Neural Inverse Rendering
Although the ambiguity is alleviated on non-Lambertian objects, the problem is still difficult to solve for more general objects with complex shapes introducing irregular shadows and general materials with complex reflectance like anisotropic reflectance.
Video Question Answering Using CLIP-Guided Visual-Text Attention
Specifically, we first extract video features using a TimeSformer and text features using a BERT from the target application domain, and utilize CLIP to extract a pair of visual-text features from the general-knowledge domain through the domain-specific learning.
MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
However, since the target objects in these existing datasets are usually relatively salient, dominant, and isolated, VOS under complex scenes has rarely been studied.
Decomposing 3D Neuroimaging into 2+1D Processing for Schizophrenia Recognition
Deep learning has been successfully applied to recognizing both natural images and medical images.
Robust Reflection Removal with Flash-only Cues in the Wild
We propose a simple yet effective reflection-free cue for robust reflection removal from a pair of flash and ambient (no-flash) images.
Self-Regularized Prototypical Network for Few-Shot Semantic Segmentation
A direct yet effective prototype regularization on support set is proposed in SRPNet, in which the generated prototypes are evaluated and regularized on the support set itself.
VLT: Vision-Language Transformer and Query Generation for Referring Segmentation
We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features.
Ranked #1 on
Referring Video Object Segmentation
on Refer-YouTube-VOS
(using extra training data)
Referring Expression Segmentation
Referring Video Object Segmentation
Boosting the Discriminant Power of Naive Bayes
In this paper, we propose a feature augmentation method employing a stack auto-encoder to reduce the noise in the data and boost the discriminant power of naive Bayes.
A Max-relevance-min-divergence Criterion for Data Discretization with Applications on Naive Bayes
Thus, we propose a Max-Dependency-Min-Divergence (MDmD) criterion that maximizes both the discriminant information and generalization ability of the discretized data.
NeIF: Representing General Reflectance as Neural Intrinsics Fields for Uncalibrated Photometric Stereo
Uncalibrated photometric stereo (UPS) is challenging due to the inherent ambiguity brought by unknown light.
Spatial Feature Mapping for 6DoF Object Pose Estimation
To address the problem of rotation symmetry ambiguity for objects, a spherical convolution is utilized and the spherical features are combined with the convolutional features that are mapped to the graph.
Instance-Specific Feature Propagation for Referring Segmentation
In this work, we propose a novel framework that simultaneously detects the target-of-interest via feature propagation and generates a fine-grained segmentation mask.
Attention-based Dual-stream Vision Transformer for Radar Gait Recognition
Radar gait recognition is robust to light variations and less infringement on privacy.
Two-stage Rule-induction Visual Reasoning on RPMs with an Application to Video Prediction
Based on the two intrinsic natures of RPM problem, visual recognition and logical reasoning, we propose a Two-stage Rule-Induction Visual Reasoner (TRIVR), which consists of a perception module and a reasoning module, to tackle the challenges of real-world visual recognition and subsequent logical reasoning tasks, respectively.
Human Activity Recognition Using 3D Orthogonally-projected EfficientNet on Radar Time-Range-Doppler Signature
In radar activity recognition, 2D signal representations such as spectrogram, cepstrum and cadence velocity diagram are often utilized, while range information is often neglected.
Vision-Language Transformer and Query Generation for Referring Segmentation
We introduce transformer and multi-head attention to build a network with an encoder-decoder attention mechanism architecture that "queries" the given image with the language expression.
Ranked #4 on
Referring Expression Segmentation
on RefCOCOg-test
Complex common spatial patterns on time-frequency decomposed EEG for brain-computer interface
We propose a novel approach called time-frequency common spatial patterns (TFCSP) to enhance the robustness and accuracy of the electroencephalogram (EEG) signal classification.
Single Image Reflection Removal With Absorption Effect
In this paper, we consider the absorption effect for the problem of single image reflection removal.
Panoramic Image Reflection Removal
This paper studies the problem of panoramic image reflection removal, aiming at reliving the content ambiguity between reflection and transmission scenes.
Knowledge-aware Deep Framework for Collaborative Skin Lesion Segmentation and Melanoma Recognition
In this paper, we propose a novel knowledge-aware deep framework that incorporates some clinical knowledge into collaborative learning of two important melanoma diagnosis tasks, i. e., skin lesion segmentation and melanoma recognition.
Towards Enhancing Fine-grained Details for Image Matting
In this paper, we argue that recovering these microscopic details relies on low-level but high-definition texture features.
Interaction via Bi-Directional Graph of Semantic Region Affinity for Scene Parsing
In this work, we treat each respective region in an image as a whole, and capture the structure topology as well as the affinity among different regions.
Feature Distillation With Guided Adversarial Contrastive Learning
In this paper, we propose a novel approach called Guided Adversarial Contrastive Distillation (GACD), to effectively transfer adversarial robustness from teacher to student with features.
Temporal Distinct Representation Learning for Action Recognition
Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos.
Brain MRI-based 3D Convolutional Neural Networks for Classification of Schizophrenia and Controls
Convolutional Neural Network (CNN) has been successfully applied on classification of both natural images and medical images but not yet been applied to differentiating patients with schizophrenia from healthy controls.
Object 6D Pose Estimation with Non-local Attention
In this paper, we address the challenging task of estimating 6D object pose from a single RGB image.
Bi-directional Dermoscopic Feature Learning and Multi-scale Consistent Decision Fusion for Skin Lesion Segmentation
Accurate segmentation of skin lesion from dermoscopic images is a crucial part of computer-aided diagnosis of melanoma.
Semantic Correlation Promoted Shape-Variant Context for Segmentation
In this way, the proposed network aggregates the context information of a pixel from its semantic-correlated region instead of a predefined fixed region.
Ranked #16 on
Semantic Segmentation
on COCO-Stuff test
Boundary-Aware Feature Propagation for Scene Segmentation
Furthermore, we propose a boundary-aware feature propagation (BFP) module to harvest and propagate the local features within their regions isolated by the learned boundaries in the UAG-structured image.
Ranked #36 on
Semantic Segmentation
on Cityscapes test
SPLINE-Net: Sparse Photometric Stereo through Lighting Interpolation and Normal Estimation Networks
This paper solves the Sparse Photometric stereo through Lighting Interpolation and Normal Estimation using a generative Network (SPLINE-Net).
Toward Achieving Robust Low-Level and High-Level Scene Parsing
Furthermore, we introduce a “dense skip” architecture to retain a rich set of low-level information from the pre-trained CNN, which is essential to improve the low-level parsing performance.
Feature Boosting Network For 3D Pose Estimation
Learning a set of features that are reliable and discriminatively representative of the pose of a hand (or body) part is difficult due to the ambiguities, texture and illumination variation, and self-occlusion in the real application of 3D pose estimation.
Interest Point Detection based on Adaptive Ternary Coding
In this paper, an adaptive pixel ternary coding mechanism is proposed and a contrast invariant and noise resistant interest point detector is developed on the basis of this mechanism.
DCI: Discriminative and Contrast Invertible Descriptor
In this paper, we proposed a Discriminative and Contrast Invertible (DCI) local feature descriptor.
Deformable Pose Traversal Convolution for 3D Action and Gesture Recognition
This deformable convolution can better utilize contextual joints for action and gesture recognition and is more robust to noisy joints.
Context Contrasted Feature and Gated Multi-Scale Aggregation for Scene Segmentation
In this paper, we first propose a novel context contrasted local feature that not only leverages the informative context but also spotlights the local information in contrast to the context.
Ranked #19 on
Semantic Segmentation
on COCO-Stuff test
Feature Weighting and Regularization of Common Spatial Patterns in EEG-Based Motor Imagery BCI
Electroencephalography signals have very low spatial resolution and electrodes capture signals that are overlapping each other.
