Search Results for author:
Found 15 papers, 11 papers with code
PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation
In this work, we address this limitation by studying camera-based 3D panoptic segmentation, aiming to achieve a unified occupancy representation for camera-only 3D scene understanding.
detrex: Benchmarking Detection Transformers
To address this issue, we develop a unified, highly modular, and lightweight codebase called detrex, which supports a majority of the mainstream DETR-based instance recognition algorithms, covering various fundamental tasks, including object detection, segmentation, and pose estimation.
SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model
Skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases, impacting a considerable portion of the population.
Optimization of binding affinities in chemical space with generative pretrained transformer and deep reinforcement learning
The SGPT-RL method achieved better results than Reinvent on the ACE2 task, where molecular docking was used as the optimization goal.
Introducing Depth into Transformer-based 3D Object Detection
To address the second issue, we introduce an auxiliary learning task called Depth-aware Negative Suppression loss.
Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare
Revoking personal private data is one of the basic human rights, which has already been sheltered by several privacy-preserving laws in many countries.
Semi-Supervised Domain Generalizable Person Re-Identification
Instead, we aim to explore multiple labeled datasets to learn generalized domain-invariant representations for person re-id, which is expected universally effective for each new-coming re-id scenario.
Ranked #16 on
Person Re-Identification
on Market-1501
(using extra training data)
Generalizable Person Re-identification
Knowledge Distillation
+1
Learning Instance-level Spatial-Temporal Patterns for Person Re-identification
In this paper, we propose a novel Instance-level and Spatial-Temporal Disentangled Re-ID method (InSTD), to improve Re-ID accuracy.
Ranked #14 on
Person Re-Identification
on DukeMTMC-reID
Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification
Given the input person image, the ensemble method would focus on the head-shoulder feature by assigning a larger weight if the individual insides the image is in black clothing.
FastReID: A Pytorch Toolbox for General Instance Re-identification
General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identification, face recognition, wildlife protection, commodity tracing, and snapshop, etc.. To meet the increasing application demand for general instance re-identification, we present FastReID as a widely used software system in JD AI Research.
Ranked #1 on
Person Re-Identification
on MSMT17-C
DMFTwDFT: An open-source code combining Dynamical Mean Field Theory with various Density Functional Theory packages
The existence of this library allows developers of other DFT codes to interface with our package and achieve the charge-self-consistency within DFT+DMFT loops.
Strongly Correlated Electrons
A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification
The present study collects and evaluates these effective training tricks in person ReID.
Ranked #44 on
Person Re-Identification
on DukeMTMC-reID
Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification
FPR uses the error from robust reconstruction over spatial pyramid features to measure similarities between two persons.
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
In the literature, some effective training tricks are briefly appeared in several papers or source codes.
Ranked #2 on
Person Re-Identification
on UAV-Human
Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention
Video-based person re-identification (ReID) is a challenging problem, where some video tracks of people across non-overlapping cameras are available for matching.
