Search Results for author:
Found 25 papers, 11 papers with code
VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results
Results of 33 object detection algorithms are presented.
Evidential Detection and Tracking Collaboration: New Problem, Benchmark and Algorithm for Robust Anti-UAV System
Still, previous works have simplified such an anti-UAV task as a tracking problem, where the prior information of UAVs is always provided; such a scheme fails in real-world anti-UAV tasks (i. e. complex scenes, indeterminate-appear and -reappear UAVs, and real-time UAV surveillance).
AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression
With the proposed body representation, we further deliver a compact single-stage multi-person pose regression network, termed as AdaptivePose.
P$^{2}$Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation
Furthermore, because those textureless regions in indoor scenes (e. g., wall, floor, roof, \etc) usually correspond to planar regions, we propose to leverage superpixels as a plane prior.
P²Net: Patch-match and Plane-regularization for Unsupervised Indoor Depth Estimation
The task is extremely challenging because of the vast areas of non-texture regions in these scenes.
Towards End-to-end Semi-supervised Learning for One-stage Object Detection
In addition to this challenge, we also reveal two key issues in one-stage SSOD, which are low-quality pseudo-labeling and multi-task optimization conflict, respectively.
QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query
The existing end-to-end methods rely on dense representations to preserve the spatial detail and structure for precise keypoint localization.
UniParser: Multi-Human Parsing with Unified Correlation Representation Learning
Multi-human parsing is an image segmentation task necessitating both instance-level and fine-grained category-level information.
Ranked #1 on
Multi-Human Parsing
on MHP v2.0
DiffCR: A Fast Conditional Diffusion Framework for Cloud Removal from Optical Satellite Images
Optical satellite images are a critical data source; however, cloud cover often compromises their quality, hindering image applications and analysis.
Single-stage Multi-human Parsing via Point Sets and Center-based Offsets
We instead present a high-performance Single-stage Multi-human Parsing (SMP) deep architecture that decouples the multi-human parsing problem into two fine-grained sub-problems, i. e., locating the human body and parts.
Ranked #2 on
Multi-Human Parsing
on MHP v2.0
Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos
Accurate classification of embryo early development stages can provide embryologists valuable information for assessing the embryo quality, and hence is critical to the success of IVF.
In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics
Tens of millions of women suffer from infertility worldwide each year.
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery
Motivated by the correlation between the depth and the geometric structure of a 360 indoor image, we propose a novel learning-based depth estimation framework that leverages the geometric structure of a scene to conduct depth estimation.
Ranked #16 on
Depth Estimation
on Stanford2D3D Panoramic
Mean dimension and a non-embeddable example for amenable group actions
For every infinite (countable discrete) amenable group $G$ and every positive integer $d$ we construct a minimal $G$-action of mean dimension $d/2$ which cannot be embedded in the full $G$-shift on $([0, 1]^d)^G$.
Dynamical Systems
Mean dimension of product spaces: a fundamental formula
However, there is still one longstanding problem which remains open in this direction, asking if there exists a continuous action of $G$ on some compact metrizable space $X$ such that $\mathrm{mdim}(X\times X, G)<2\cdot\mathrm{mdim}(X, G)$.
Dynamical Systems
The Hilbert cube contains a minimal subshift of full mean dimension
We construct a minimal dynamical system of mean dimension equal to $1$, which can be embedded in the shift action on the Hilbert cube $[0, 1]^\mathbb{Z}$.
Dynamical Systems
Prior Based Human Completion
One is a structure prior, it uses a human parsing map to represent the human body structure.
The 2nd Anti-UAV Workshop & Challenge: Methods and Results
The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking.
A Multi-scale Graph Network with Multi-head Attention for Histopathology Image Diagnosis
The proposed method is featured by a pyramid graph structure and an attention-based multi-instance learning strategy.
Learning Quality-aware Representation for Multi-person Pose Regression
Off-the-shelf single-stage multi-person pose regression methods generally leverage the instance score (i. e., confidence of the instance localization) to indicate the pose quality for selecting the pose candidates.
Single-Stage Is Enough: Multi-Person Absolute 3D Pose Estimation
The existing multi-person absolute 3D pose estimation methods are mainly based on two-stage paradigm, i. e., top-down or bottom-up, leading to redundant pipelines with high computation cost.
The 3rd Anti-UAV Workshop & Challenge: Methods and Results
Second, we set up two tracks for the first time, i. e., Anti-UAV Tracking and Anti-UAV Detection & Tracking.
RefCLIP: A Universal Teacher for Weakly Supervised Referring Expression Comprehension
Based on RefCLIP, we further propose the first model-agnostic weakly supervised training scheme for existing REC models, where RefCLIP acts as a mature teacher to generate pseudo-labels for teaching common REC models.
Unified Single-Stage Transformer Network for Efficient RGB-T Tracking
With this structure, the network can extract fusion features of the template and search region under the mutual interaction of modalities.
Ranked #1 on
Rgb-T Tracking
on GTOT
The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
In the attack, one can construct a PII association task, whereby an LLM is fine-tuned using a minuscule PII dataset, to potentially reinstate and reveal concealed PIIs.
