Search Results for author:
Found 21 papers, 4 papers with code
DSAGL: Dual-Stream Attention-Guided Learning for Weakly Supervised Whole Slide Image Classification
Whole-slide images (WSIs) are critical for cancer diagnosis due to their ultra-high resolution and rich semantic content.
CoProSketch: Controllable and Progressive Sketch Generation with Diffusion Model
We propose a novel framework CoProSketch, providing prominent controllability and details for sketch generation with diffusion models.
OpticFusion: Multi-Modal Neural Implicit 3D Reconstruction of Microstructures by Fusing White Light Interferometry and Optical Microscopy
However, conventional WLI cannot capture the natural color of a sample's surface, which is essential for many microscale research applications that require both 3D geometry and color information.
GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking
Specifically, we propose a novel framework that constructs a pseudo 4D Gaussian field with dense 3D point tracking and renders the Gaussian field for all video frames.
GS-DiT: Advancing Video Generation with Dynamic 3D Gaussian Fields through Efficient Dense 3D Point Tracking
Inspired by Monocular Dynamic novel View Synthesis (MDVS) that optimizes a 4D representation and renders videos according to different 4D elements, such as camera pose and object motion editing, we bring dynamic 3D Gaussian fields to video generation.
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding
We integrate pose embedding to encapsulate information such as multi-view camera poses, providing implicit geometric constraints for multi-view disparity feature fusion dominated by attention.
ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
On the YFCC100M dataset, our matching accuracy is competitive with LoFTR, a state-of-the-art transformer-based architecture, while the inference speed is boosted to 4 times, even outperforming the CNN-based methods.
BlinkVision: A Benchmark for Optical Flow, Scene Flow and Point Tracking Estimation using RGB Frames and Events
BlinkVision enables extensive benchmarks on three types of correspondence tasks (optical flow, point tracking, and scene flow estimation) for both image-based and event-based methods, offering new observations, practices, and insights for future research.
BlinkTrack: Feature Tracking over 100 FPS via Events and Images
Feature tracking is crucial for, structure from motion (SFM), simultaneous localization and mapping (SLAM), object tracking and various computer vision tasks.
Multi-View Neural 3D Reconstruction of Micro-/Nanostructures with Atomic Force Microscopy
However, conventional AFM scanning struggles to reconstruct complex 3D micro-/nanostructures precisely due to limitations such as incomplete sample topography capturing and tip-sample convolution artifacts.
Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor
Specifically, we propose a multi-modal implicit scene representation that supports rendering both the signals from the RGB camera and light-weight ToF sensor which drives the optimization by comparing with the raw sensor inputs.
Graph-based Asynchronous Event Processing for Rapid Object Recognition
Different from traditional video cameras, event cameras capture asynchronous events stream in which each event encodes pixel location, trigger time, and the polarity of the brightness changes.
FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow
This paper introduces a novel transformer-based network architecture, FlowFormer, along with the Masked Cost Volume AutoEncoding (MCVA) for pretraining it to tackle the problem of optical flow estimation.
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features
We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos.
DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation
In addition to the scene generation, the final part of DiffInDScene can be used as a post-processing module to refine the 3D reconstruction results from multi-view stereo.
PATS: Patch Area Transportation with Subdivision for Local Feature Matching
However, estimating scale differences between these patches is non-trivial since the scale differences are determined by both relative camera poses and scene structures, and thus spatially varying over image pairs.
BlinkFlow: A Dataset to Push the Limits of Event-based Optical Flow Estimation
Experiments show that BlinkFlow improves the generalization performance of state-of-the-art methods by more than 40\% on average and up to 90\%.
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image
Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-energy and have been massively deployed on mobile devices for the purposes like autofocus, obstacle detection, etc.
Neural Rendering in a Room: Amodal 3D Understanding and Free-Viewpoint Rendering for the Closed Scene Composed of Pre-Captured Objects
We, as human beings, can understand and picture a familiar scene from arbitrary viewpoints given a single image, whereas this is still a grand challenge for computers.
Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering
In this paper, we present a novel neural scene rendering system, which learns an object-compositional neural radiance field and produces realistic rendering with editing capability for a clustered and real-world scene.
VS-Net: Voting with Segmentation for Visual Localization
To address this problem, we propose a novel visual localization framework that establishes 2D-to-3D correspondences between the query image and the 3D map with a series of learnable scene-specific landmarks.
