Search Results for author:
Found 28 papers, 6 papers with code
Cross-Modality Transformer for Visible-Infrared Person Re-Identification
To alleviate the above issues, we propose a novel Cross-Modality Transformer (CMT) to jointly explore a modality-level alignment module and an instance-level module for VI-ReID.
A Keypoint-based Global Association Network for Lane Detection
Earlier works follow a top-down roadmap to regress predefined anchors into various shapes of lane lines, which lacks enough flexibility to fit complex shapes of lanes due to the fixed anchor shapes.
Ranked #3 on
Lane Detection
on TuSimple
(F1 score metric)
Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition
To address this issue, we propose an end-to-end Motion-modulated Temporal Fragment Alignment Network (MTFAN) by jointly exploring the task-specific motion modulation and the multi-level temporal fragment alignment for Few-Shot Action Recognition (FSAR).
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking
To address this issue, segmentation-based trackers have been proposed that employ per-pixel matching to improve the tracking performance of deformable objects effectively.
Geometry Uncertainty Projection Network for Monocular 3D Object Detection
In this paper, we propose a Geometry Uncertainty Projection Network (GUP Net) to tackle the error amplification problem at both inference and training stages.
Lesion-Aware Transformers for Diabetic Retinopathy Grading
First, to the best of our knowledge, this is the first work to formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder.
Uncertainty Guided Collaborative Training for Weakly Supervised Temporal Action Detection
To alleviate this problem, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other.
Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
To address these issues, we propose a novel end-to-end Part-Aware Transformer (PAT) for occluded person Re-ID through diverse part discovery via a transformer encoderdecoder architecture, including a pixel context based transformer encoder and a part prototype based transformer decoder.
Action Unit Memory Network for Weakly Supervised Temporal Action Localization
In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.
Ranked #5 on
Weakly Supervised Action Localization
on THUMOS14
Weakly Supervised Action Localization
Weakly-supervised Temporal Action Localization
+1
Foreground Activation Maps for Weakly Supervised Object Localization
To the best of our knowledge, this is the first work that can achieve remarkable performance for both tasks by optimizing them jointly via FAM for WSOL.
Meta-Attack: Class-Agnostic and Model-Agnostic Physical Adversarial Attack
To tackle these issues, we propose a class-agnostic and model-agnostic physical adversarial attack model (Meta-Attack), which is able to not only generate robust physical adversarial examples by simulating color and shape distortions, but also generalize to attacking novel images and novel DNN models by accessing a few digital and physical images.
Task-Aware Part Mining Network for Few-Shot Learning
The task-aware part filters can adapt to any individual task and automatically mine task-related local parts even for an unseen task.
Robust Collaborative Learning of Patch-level and Image-level Annotations for Diabetic Retinopathy Grading from Fundus Image
As a result, it exploits more discriminative features for DR grading.
Graph Structured Network for Image-Text Matching
The GSMN explicitly models object, relation and attribute as a structured phrase, which not only allows to learn correspondence of object, relation and attribute separately, but also benefits to learn fine-grained correspondence of structured phrase.
Ranked #13 on
Cross-Modal Retrieval
on Flickr30k
Cross-modality Person re-identification with Shared-Specific Feature Transfer
In this paper, we tackle the above limitation by proposing a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and the modality-specific characteristics to boost the re-identification performance.
Cross-Modality Person Re-identification
Person Re-Identification
RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
First, it can exploit pixel alignment and feature alignment jointly.
Cross-Modality Person Re-identification
Person Re-Identification
+1
I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs
To effectively leverage the knowledge graph, we design a novel Two-Stream Graph Convolutional Network (TS-GCN) consisting of a classifier branch and an instance branch.
Ranked #4 on
Zero-Shot Action Recognition
on Olympics
Exploring Feature Representation and Training strategies in Temporal Action Localization
Temporal action localization has recently attracted significant interest in the Computer Vision community.
Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking
To refine the states of the target and re-track the target when it is back to view from heavy occlusion and out of view, we elaborately design a novel subnetwork to learn the target-driven visual attentions from the guidance of both visual and natural language cues.
Joint Pose and Expression Modeling for Facial Expression Recognition
First, the encoder-decoder structure of the generator can learn a generative and discriminative identity representation for face images.
Multi-Task Correlation Particle Filter for Robust Object Tracking
In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual tracking.
3D Part-Based Sparse Tracker With Automatic Synchronization and Registration
In this paper, we present a part-based sparse tracker in a particle filter framework where both the motion and appearance model are formulated in 3D.
Structural Correlation Filter for Robust Visual Tracking
In this paper, we propose a novel structural correlation filter (SCF) model for robust visual tracking.
In Defense of Sparse Tracking: Circulant Sparse Tracker
Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework.
Structural Sparse Tracking
Sparse representation has been applied to visual tracking by finding the best target candidate with minimal reconstruction error by use of target templates.
Partial Occlusion Handling for Visual Tracking via Robust Part Matching
The proposed part matching tracker (PMT) has a number of attractive properties.
ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images
The task is to identify the inlier features and establish their consistent correspondences across the image set.
