Search Results for author:
Found 15 papers, 7 papers with code
SceneTracker: Long-term Scene Flow Estimation Network
Considering the complementarity of scene flow estimation in the spatial domain's focusing capability and 3D object tracking in the temporal domain's coherence, this study aims to address a comprehensive new task that can simultaneously capture fine-grained and long-term 3D motion in an online manner: long-term scene flow estimation (LSFE).
Few-shot Class-incremental Learning: A Survey
In our in-depth examination, we delve into various facets of FSCIL, encompassing the problem definition, the discussion of the primary challenges of unreliable empirical risk minimization and the stability-plasticity dilemma, general schemes, and relevant problems of IL and Few-shot Learning (FSL).
Class-Incremental Object Detection
Few-Shot Class-Incremental Learning
+4
GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer
They seek correspondences over downsampled superpoints, which are then propagated to dense points.
Ranked #5 on
Point Cloud Registration
on FP-O-H
RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo
In particular, we propose RayMVSNet which learns sequential prediction of a 1D implicit field along each camera ray with the zero-crossing point indicating scene depth.
SplatFlow: Learning Multi-frame Optical Flow via Splatting
The occlusion problem remains a crucial challenge in optical flow estimation (OFE).
A Forward and Backward Compatible Framework for Few-shot Class-incremental Pill Recognition
In forward-compatible learning, we propose an innovative virtual class synthesis strategy and a Center-Triplet (CT) loss to enhance discriminative feature learning.
Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearance, obvious intraclass variation, small size and serious background's interference.
Pixel Difference Networks for Efficient Edge Detection
A faster version of PiDiNet with less than 0. 1M parameters can still achieve comparable performance among state of the arts with 200 FPS.
Ranked #2 on
Edge Detection
on BRIND
Frequency-specific segregation and integration of human cerebral cortex: an intrinsic functional atlas
The frequency-specific coupling mechanism of the functional human brain networks underpins its complex cognitive and behavioral functions.
A Pose-only Solution to Visual Reconstruction and Navigation
Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment.
Deep Learning for Scene Classification: A Survey
Scene classification, aiming at classifying a scene image to one of the predefined scene categories by comprehending the entire image, is a longstanding, fundamental and challenging problem in computer vision.
FTBNN: Rethinking Non-linearity for 1-bit CNNs and Going Beyond
Binary neural networks (BNNs), where both weights and activations are binarized into 1 bit, have been widely studied in recent years due to its great benefit of highly accelerated computation and substantially reduced memory footprint that appeal to the development of resource constrained devices.
Dynamic Group Convolution for Accelerating Convolutional Neural Networks
In this paper, we propose dynamic group convolution (DGC) that adaptively selects which part of input channels to be connected within each group for individual samples on the fly.
Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multi-view Learning
More interestingly, some linear transformation based complete multi-view methods can be adapted to IML directly with the guidance of the framework.
Secure Classification With Augmented Features
It provides various candidate classifiers to meet the following assumption of security operation.
