Search Results for author:
Found 12 papers, 5 papers with code
DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation
Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed.
Shape-Erased Feature Learning for Visible-Infrared Person Re-Identification
To this end, we propose shape-erased feature learning paradigm that decorrelates modality-shared features in two orthogonal subspaces.
Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval
To address this problem, we propose a Text-Adaptive Multiple Visual Prototype Matching model, which automatically captures multiple prototypes to describe a video by adaptive aggregation of video token features.
Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentification
To learn camera-view invariant features for person Re-IDentification (Re-ID), the cross-camera image pairs of each person play an important role.
Letter-level Online Writer Identification
To make the application of writer-id more practical (e. g., on mobile devices), we focus on a novel problem, letter-level online writer-id, which requires only a few trajectories of written letters as identification cues.
Cross-Camera Feature Prediction for Intra-Camera Supervised Person Re-identification across Distant Scenes
To learn camera-invariant representation from cross-camera unpaired training data, we propose a cross-camera feature prediction method to mine cross-camera self supervision information from camera-specific feature distribution by transforming fake cross-camera positive feature pairs and minimize the distances of the fake pairs.
Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification
Recently, person re-identification (Re-ID) has achieved great progress.
Ranked #3 on
Person Re-Identification
on PRCC
One for More: Selecting Generalizable Samples for Generalizable ReID Model
Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the performance on samples outside the batch.
Unsupervised Person Re-Identification by Camera-Aware Similarity Consistency Learning
To alleviate the effect of cross-camera scene variation, we propose a Camera-Aware Similarity Consistency Loss to learn consistent pairwise similarity distributions for intra-camera matching and cross-camera matching.
Distilled Person Re-Identification: Towards a More Scalable System
To solve these problems in a unified system, we propose a Multi-teacher Adaptive Similarity Distillation Framework, which requires only a few labelled identities of target domain to transfer knowledge from multiple teacher models to a user-specified lightweight student model without accessing source domain data.
RGB-Infrared Cross-Modality Person Re-Identification
To that end, matching RGB images with infrared images is required, which are heterogeneous with very different visual characteristics.
Ranked #4 on
Cross-Modal Person Re-Identification
on SYSU-MM01
(mAP (All-search & Single-shot) metric)
Cross-Modality Person Re-identification
Cross-Modal Person Re-Identification
Robust Depth-based Person Re-identification
More specifically, we exploit depth voxel covariance descriptor and further propose a locally rotation invariant depth shape descriptor called Eigen-depth feature to describe pedestrian body shape.
