Search Results for author:
Found 30 papers, 10 papers with code
RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction
Recently, neural implicit surfaces have become popular for multi-view reconstruction.
Adjacent-level Feature Cross-Fusion with 3D CNN for Remote Sensing Image Change Detection
First, through the inner fusion property of 3D convolution, we design a new feature fusion way that can simultaneously extract and fuse the feature information from bi-temporal images.
Exploiting Neighborhood Structural Features for Change Detection
In this letter, a novel method for change detection is proposed using neighborhood structure correlation.
Learning Discretized Neural Networks under Ricci Flow
We propose an analysis that this mismatch can be viewed as a metric perturbation in a Riemannian manifold through the lens of duality theory.
Revisiting the Spatial and Temporal Modeling for Few-shot Action Recognition
In this paper, we propose SloshNet, a new framework that revisits the spatial and temporal modeling for few-shot action recognition in a finer manner.
BSNet: Lane Detection via Draw B-spline Curves Nearby
The locality of lane representation is the ability to modify lanes locally which can simplify parameter optimization.
E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Context
However, the redundant parameters within the network structure can cause a large model size when scaling up for desirable performance.
Dynamically Stable Poincaré Embeddings for Neural Manifolds
As a result, we prove that, if initial metrics have an $L^2$-norm perturbation which deviates from the Hyperbolic metric on the Poincar\'e ball, the scaled Ricci-DeTurck flow of such metrics smoothly and exponentially converges to the Hyperbolic metric.
A Simple Long-Tailed Recognition Baseline via Vision-Language Model
Recent advances in large-scale contrastive visual-language pretraining shed light on a new pathway for visual recognition.
Ranked #2 on
Long-tail Learning
on Places-LT
(using extra training data)
MaIL: A Unified Mask-Image-Language Trimodal Network for Referring Image Segmentation
Referring image segmentation is a typical multi-modal task, which aims at generating a binary mask for referent described in given language expressions.
Ranked #1 on
Referring Expression Segmentation
on G-Ref test B
Explicitly Modeling the Discriminability for Instance-Aware Visual Object Tracking
Visual object tracking performance has been dramatically improved in recent years, but some severe challenges remain open, like distractors and occlusions.
ActionCLIP: A New Paradigm for Video Action Recognition
Moreover, to handle the deficiency of label texts and make use of tremendous web data, we propose a new paradigm based on this multimodal learning framework for action recognition, which we dub "pre-train, prompt and fine-tune".
Ranked #2 on
Action Recognition In Videos
on Kinetics-400
Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation
Meanwhile, to guarantee that the day and night images contain the same information, the domain-separated network takes the day-time images and corresponding night-time images (generated by GAN) as input, and the private and invariant feature extractors are learned by orthogonality and similarity loss, where the domain gap can be alleviated, thus better depth maps can be expected.
TransVOS: Video Object Segmentation with Transformers
Recently, Space-Time Memory Network (STM) based methods have achieved state-of-the-art performance in semi-supervised video object segmentation (VOS).
One-shot visual object segmentation
Semantic Segmentation
+1
One-shot Face Reenactment Using Appearance Adaptive Normalization
The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a driving image) while keeping its original appearance.
Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation
In this paper we tackle the problem of pose guided person image generation, which aims to transfer a person image from the source pose to a novel target pose while maintaining the source appearance.
RFNet: Recurrent Forward Network for Dense Point Cloud Completion
The RFE extracts multiple global features from the incomplete point clouds for different recurrent levels, and the FDC generates point clouds in a coarse-to-fine pipeline.
FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion
Then, a refined depth map is further obtained using a residual learning strategy in the coarse-to-fine stage with a coarse depth map and color image as input.
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation
To obtainmore accurate depth estimation in large gradient regions, itis necessary to obtain high-resolution features with spatialand semantic information.
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition
Second, the parameter frequency distribution is further adopted to guide the student network to learn the appearance modeling process from the teacher.
Semantic Graph Based Place Recognition for 3D Point Clouds
First, we propose a novel semantic graph representation for the point cloud scenes by reserving the semantic and topological information of the raw point cloud.
DTVNet: Dynamic Time-lapse Video Generation via Single Still Image
The proposed DTVNet consists of two submodules: \emph{Optical Flow Encoder} (OFE) and \emph{Dynamic Video Generator} (DVG).
The 'Letter' Distribution in the Chinese Language
In addition, we collected Chinese literature corpora for different historical periods from the Tang Dynasty to the present, and we dismantled the Chinese written language into three kinds of basic particles: characters, strokes and constructive parts.
Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose
On the one hand, we adopt the deforming autoencoder to disentangle identity and pose representations.
Extended Feature Pyramid Network for Small Object Detection
Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.
STM: SpatioTemporal and Motion Encoding for Action Recognition
Spatiotemporal and motion features are two complementary and crucial information for video action recognition.
Ranked #1 on
Action Recognition In Videos
on HMDB-51
FReeNet: Multi-Identity Face Reenactment
This paper presents a novel multi-identity face reenactment framework, named FReeNet, to transfer facial expressions from an arbitrary source face to a target face with a shared model.
Real-time 3D Human Tracking for Mobile Robots with Multisensors
An ultrasonic sensor array is employed to provide the range information from the target person to the robot and Gaussian Process Regression is used for partial location estimation (2-D).
Large Margin Object Tracking with Circulant Feature Maps
Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently.
Robust Object Tracking with a Hierarchical Ensemble Framework
A discriminative model which accounts for the matching degree of local patches is adopted via a bottom ensemble layer, and a generative model which exploits holistic templates is used to search for the object through the middle ensemble layer as well as an adaptive Kalman filter.
