Search Results for author:
Found 66 papers, 22 papers with code
Disentangle Your Dense Object Detector
Extensive experiments on MS COCO benchmark show that our approach can lead to 2. 0 mAP, 2. 4 mAP and 2. 2 mAP absolute improvements on RetinaNet, FCOS, and ATSS baselines with negligible extra overhead.
ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
In the realm of large multi-modal models (LMMs), efficient modality alignment is crucial yet often constrained by the scarcity of high-quality image-text data.
Ranked #1 on
visual instruction following
on LLaVA-Bench
P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds
Specifically, we first sample seeds from the point clouds in template and search area respectively.
Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models
Open-sourced Large Language Models (LLMs) have achieved great success in various NLP tasks, however, they are still far inferior to API-based models when acting as agents.
T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step
Based on that, we further introduce T-Eval to evaluate the tool utilization capability step by step.
AutoAlignV2: Deformable Feature Aggregation for Dynamic Multi-Modal 3D Object Detection
Recently, AutoAlign presents a learnable paradigm in combining these two modalities for 3D object detection.
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
Instead of directly training a depth prediction network, we unify the image and LiDAR features in the Bird-Eye-View (BEV) space and adaptively transfer knowledge across non-homogenous representations in a teacher-student paradigm.
Ranked #14 on
3D Object Detection
on nuScenes Camera Only
Are We on the Right Way for Evaluating Large Vision-Language Models?
We evaluate 16 leading LVLMs on MMStar to assess their multi-modal capabilities, and on 7 benchmarks with the proposed metrics to investigate their data leakage and actual multi-modal gain.
MMNet: Muscle motion-guided network for micro-expression recognition
By adding the position embeddings of the face generated by PC module at the end of the two branches, the PC module can help to add position information to facial muscle motion pattern features for the MER.
Micro Expression Recognition
Micro-Expression Recognition
+1
Towards Fine-grained Large Object Segmentation 1st Place Solution to 3D AI Challenge 2020 -- Instance Segmentation Track
This technical report introduces our solutions of Team 'FineGrainedSeg' for Instance Segmentation track in 3D AI Challenge 2020.
Bijective Mapping Network for Shadow Removal
Shadow removal, which aims to restore the background in the shadow regions, is challenging due to the highly ill-posed nature.
Ultra-High Resolution Segmentation with Ultra-Rich Context: A Novel Benchmark
With the increasing interest and rapid development of methods for Ultra-High Resolution (UHR) segmentation, a large-scale benchmark covering a wide range of scenes with full fine-grained dense annotations is urgently needed to facilitate the field.
Ranked #1 on
Semantic Segmentation
on INRIA Aerial Image Labeling
(mIOU metric)
Domain-Unified Prompt Representations for Source-Free Domain Generalization
The proposed scheme generates diverse prompts from a domain bank that contains many more diverse domains than existing DG datasets.
Empowering Low-Light Image Enhancer through Customized Learnable Priors
In this work, we propose a paradigm for low-light image enhancement that explores the potential of customized learnable priors to improve the transparency of the deep unfolding paradigm.
Learning from Noisy Data for Semi-Supervised 3D Object Detection
To this end, we propose NoiseDet, a simple yet effective framework for semi-supervised 3D object detection.
Intensity-Aware Loss for Dynamic Facial Expression Recognition in the Wild
One of the main reasons is that video sequences often contain frames with different expression intensities, especially for the facial expressions in the real-world scenarios, while the images in SFER frequently present uniform and high expression intensities.
Ranked #8 on
Dynamic Facial Expression Recognition
on FERV39k
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
PsySafe: A Comprehensive Framework for Psychological-based Attack, Defense, and Evaluation of Multi-agent System Safety
In this paper, we explore these concerns through the innovative lens of agent psychology, revealing that the dark psychological states of agents constitute a significant threat to safety.
Ingredient-Oriented Multi-Degradation Learning for Image Restoration
Learning to leverage the relationship among diverse image restoration tasks is quite beneficial for unraveling the intrinsic ingredients behind the degradation.
Unleashing the Potential of Unsupervised Pre-Training with Intra-Identity Regularization for Person Re-Identification
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
High-quality Image Dehazing with Diffusion Model
The latter stage exploits the strong generation ability of DDPM to compensate for the haze-induced huge information loss, by working in conjunction with the physical modelling.
Deep Fourier Up-Sampling
Existing convolutional neural networks widely adopt spatial down-/up-sampling for multi-scale modeling.
Selective Noise Suppression Methods Using Random SVPWM to Shape the Noise Spectrum of PMSMs
Both the pulse position and switching frequency are randomized in the second method.
Structural Learning for Template-free Protein Folding
The thesis is aimed to solve the template-free protein folding problem by tackling two important components: efficient sampling in vast conformation space, and design of knowledge-based potentials with high accuracy.
MVT: Mask Vision Transformer for Facial Expression Recognition in the wild
Facial Expression Recognition (FER) in the wild is an extremely challenging task in computer vision due to variant backgrounds, low-quality facial images, and the subjectiveness of annotators.
Facial Expression Recognition
Facial Expression Recognition (FER)
MFEViT: A Robust Lightweight Transformer-based Network for Multimodal 2D+3D Facial Expression Recognition
To the best of our knowledge, this is the first work to introduce vision transformer into multimodal 2D+3D FER.
3D Facial Expression Recognition
Facial Expression Recognition
Performance-Guaranteed ODE Solvers with Complexity-Informed Neural Networks
Traditionally, we provide technical parameters for ODE solvers, such as the order, the stepsize and the local error threshold.
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection
This map enables our model to automate the alignment of non-homogenous features in a dynamic and data-driven manner.
Towards 3D Scene Reconstruction from Locally Scale-Aligned Monocular Video Depth
However, in some video-based scenarios such as video depth estimation and 3D scene reconstruction from a video, the unknown scale and shift residing in per-frame prediction may cause the depth inconsistency.
Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection
3D object detection from multiple image views is a fundamental and challenging task for visual scene understanding.
AFNet-M: Adaptive Fusion Network with Masks for 2D+3D Facial Expression Recognition
2D+3D facial expression recognition (FER) can effectively cope with illumination changes and pose variations by simultaneously merging 2D texture and more robust 3D depth information.
3D Facial Expression Recognition
Facial Expression Recognition
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
Mutual Information-Driven Pan-Sharpening
Despite the remarkable progress, existing state-of-the-art Pan-sharpening methods don't explicitly enforce the complementary information learning between two modalities of PAN and MS images.
Exposure Normalization and Compensation for Multiple-Exposure Correction
However, the procedures of correcting underexposure and overexposure to normal exposures are much different from each other, leading to large discrepancies for the network in correcting multiple exposures, thus resulting in poor performance.
Underdetermined 2D-DOD and 2D-DOA Estimation for Bistatic Coprime EMVS-MIMO Radar: From the Difference Coarray Perspective
Firstly, a 5-D tensor model was constructed by using the multi-dimensional space-time characteristics of the received data.
8D Parameters Estimation for Bistatic EMVS-MIMO Radar via the nested PARAFAC
Firstly, the outer part PARAFAC algorithm was carried out to estimate the receive spatial response matrix and its first way factor matrix.
NR-DFERNet: Noise-Robust Network for Dynamic Facial Expression Recognition
Dynamic facial expression recognition (DFER) in the wild is an extremely challenging task, due to a large number of noisy frames in the video sequences.
Ranked #9 on
Dynamic Facial Expression Recognition
on FERV39k
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
Source-Free Domain Adaptation for Real-world Image Dehazing
Although certain Domain Adaptation (DA) dehazing methods have been presented, they inevitably require access to the source dataset to reduce the gap between the source synthetic and target real domains.
Enhancement by Your Aesthetic: An Intelligible Unsupervised Personalized Enhancer for Low-Light Images
Low-light image enhancement is an inherently subjective process whose targets vary with the user's aesthetic.
CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removal
The key to shadow removal is recovering the contents of the shadow regions with the guidance of the non-shadow regions.
KSG: Knowledge and Skill Graph
This is the first study that we are aware of that looks into dynamic KSG for skill retrieval and learning.
OpticE: A Coherence Theory-Based Model for Link Prediction
During the learning process, the semantics of each entity are embedded by a vector or a point in a feature space.
A similarity measurement for time series and its application to the stock market
In this paper, for accurately describing the similarity between a pair of time series, a novel similarity measurement is proposed, which is named as the dynamic multi-perspective personalized similarity measurement (DMPSM).
Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network
Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to generate the expected high-resolution (HR) MS images, conditioning on the corresponding high-resolution PAN images.
DETRDistill: A Universal Knowledge Distillation Framework for DETR-families
Next, we propose a target-aware feature distillation to help the student model learn from the object-centric features of the teacher model.
CLIPER: A Unified Vision-Language Framework for In-the-Wild Facial Expression Recognition
Facial expression recognition (FER) is an essential task for understanding human behaviors.
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View
Based on the covariate shift assumption, we find that the gap mainly attributes to the feature distribution of BEV, which is determined by the quality of both depth estimation and 2D image's feature representation.
Novel Quality Measure and Efficient Resolution of Convex Hull Pricing for Unit Commitment
Several CH pricing methods have been presented, and a feasible cost has been used as a quality measure for the CH price.
Visual Recognition-Driven Image Restoration for Multiple Degradation With Intrinsic Semantics Recovery
Deep image recognition models suffer a significant performance drop when applied to low-quality images since they are trained on high-quality images.
Learning Sample Relationship for Exposure Correction
Exposure correction task aims to correct the underexposure and its adverse overexposure images to the normal exposure in a single network.
Cooperative IoT Data Sharing with Heterogeneity of Participants Based on Electricity Retail
With the development of Internet of Things (IoT) and big data technology, the data value is increasingly explored in multiple practical scenarios, including electricity transactions.
Guided Patch-Grouping Wavelet Transformer with Spatial Congruence for Ultra-High Resolution Segmentation
For the sake of high inference speed and low computation complexity, $\mathcal{T}$ partitions the original UHR image into patches and groups them dynamically, then learns the low-level local details with the lightweight multi-head Wavelet Transformer (WFormer) network.
Coverage Enhancement Strategy in WMSNs Based on a Novel Swarm Intelligence Algorithm: Army Ant Search Optimizer
As one of the most crucial scenarios of the Internet of Things (IoT), wireless multimedia sensor networks (WMSNs) pay more attention to the information-intensive data (e. g., audio, video, image) for remote environments.
Decomposition Ascribed Synergistic Learning for Unified Image Restoration
Learning to restore multiple image degradations within a single model is quite beneficial for real-world applications.
FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models
3D scene reconstruction is a long-standing vision task.
Exploring Temporal Frequency Spectrum in Deep Video Deblurring
Video deblurring aims to restore the latent video frames from their blurred counterparts.
Debias the Training of Diffusion Models
Diffusion models have demonstrated compelling generation quality by optimizing the variational lower bound through a simple denoising score matching loss.
RSG: Fast Learning Adaptive Skills for Quadruped Robots by Skill Graph
Developing robotic intelligent systems that can adapt quickly to unseen wild situations is one of the critical challenges in pursuing autonomous robotics.
ChangeNet: Multi-Temporal Asymmetric Change Detection Dataset
The ChangeNet dataset is suitable for both binary change detection (BCD) and semantic change detection (SCD) tasks.
Coverage Control Algorithm for DSNs Based on Improved Gravitational Search
—In directional sensor networks (DSNs), coverage control is an important way to ensure efficient communication and reliable data transmission.
Stream Query Denoising for Vectorized HD Map Construction
This paper introduces the Stream Query Denoising (SQD) strategy as a novel approach for temporal modeling in high-definition map (HD-map) construction.
Prompt Learning on Temporal Interaction Graphs
In detail, we propose a temporal prompt generator to offer temporally-aware prompts for different tasks.
A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track
In this report, we present our solution to the multi-task robustness track of the 1st Visual Continual Learning (VCL) Challenge at ICCV 2023 Workshop.
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV
In this paper, we address the challenge of multi-object tracking (MOT) in moving Unmanned Aerial Vehicle (UAV) scenarios, where irregular flight trajectories, such as hovering, turning left/right, and moving up/down, lead to significantly greater complexity compared to fixed-camera MOT.
Point-DETR3D: Leveraging Imagery Data with Spatial Point Prior for Weakly Semi-supervised 3D Object Detection
Training high-accuracy 3D detectors necessitates massive labeled 3D annotations with 7 degree-of-freedom, which is laborious and time-consuming.
GaussianCube: Structuring Gaussian Splatting using Optimal Transport for 3D Generative Modeling
To address the problem, we introduce GaussianCube, a structured GS representation that is both powerful and efficient for generative modeling.
Uncovering the Text Embedding in Text-to-Image Diffusion Models
The correspondence between input text and the generated image exhibits opacity, wherein minor textual modifications can induce substantial deviations in the generated image.
