17 citations · 46 across the 20 of their papers we have counts for
23 papers
Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration
Shiqi Zhang, Weixin Zeng, Ziheng Zhang +2
Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has revealed that some benchmarks…
MMGait: Towards Multi-Modal Gait Recognition
Chenye Wang, Qingyuan Cai, Saihui Hou +2
Gait recognition has emerged as a powerful biometric technique for identifying individuals at a distance without requiring user cooperation. Most existing methods focus primarily o…
BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition
Qingyuan Cai, Saihui Hou, Xuecai Hu +1
Gait recognition, as a reliable biometric technology, has seen rapid development in recent years while it faces significant challenges caused by diverse clothing styles in the real…
Learning Geometric Invariance for Gait Recognition
Zengbin Wang, Junjie Li, Saihui Hou +6
The goal of gait recognition is to extract identity-invariant features of an individual under various gait conditions, e.g., cross-view and cross-clothing. Most gait models strive…
FastDDHPose: Towards Unified, Efficient, and Disentangled 3D Human Pose Estimation
Qingyuan Cai, Linxin Zhang, Xuecai Hu +2
Recent approaches for monocular 3D human pose estimation (3D HPE) have achieved leading performance by directly regressing 3D poses from 2D keypoint sequences. Despite the rapid pr…
GaitSnippet: Gait Recognition Beyond Unordered Sets and Ordered Sequences
Saihui Hou, Chenye Wang, Wenpeng Lang +2
Recent advancements in gait recognition have significantly enhanced performance by treating silhouettes as either an unordered set or an ordered sequence. However, both set-based a…
OmniDiff: A Comprehensive Benchmark for Fine-grained Image Difference Captioning
Yuan Liu, Saihui Hou, Saijie Hou +3
Image Difference Captioning (IDC) aims to generate natural language descriptions of subtle differences between image pairs, requiring both precise visual change localization and co…
OpenAnimals: Revisiting Person Re-Identification for Animals Towards Better Generalization
Saihui Hou, Panjian Huang, Zengbin Wang +4
This paper addresses the challenge of animal re-identification, an emerging field that shares similarities with person re-identification but presents unique complexities due to the…
OpenGait: A Comprehensive Benchmark Study for Gait Recognition towards Better Practicality
Chao Fan, Saihui Hou, Junhao Liang +5
Gait recognition, a rapidly advancing vision technology for person identification from a distance, has made significant strides in indoor settings. However, evidence suggests that…
Disentangled Diffusion-Based 3D Human Pose Estimation with Hierarchical Spatial and Temporal Denoiser
Qingyuan Cai, Xuecai Hu, Saihui Hou +2
Recently, diffusion-based methods for monocular 3D human pose estimation have achieved state-of-the-art (SOTA) performance by directly regressing the 3D joint coordinates from the…
QAGait: Revisit Gait Recognition from a Quality Perspective
Zengbin Wang, Saihui Hou, Man Zhang +5
Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns. Silhouette modality, renowned for its easy acquisition, simpl…
FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition
Shibei Meng, Yang Fu, Saihui Hou +3
We present FastPoseGait, an open-source toolbox for pose-based gait recognition based on PyTorch. Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms…
Free Lunch for Gait Recognition: A Novel Relation Descriptor
Jilong Wang, Saihui Hou, Yan Huang +5
Gait recognition is to seek correct matches for query individuals by their unique walking patterns. However, current methods focus solely on extracting individual-specific features…
Unsupervised Gait Recognition with Selective Fusion
Xuqian Ren, Shaopeng Yang, Saihui Hou +3
Previous gait recognition methods primarily trained on labeled datasets, which require painful labeling effort. However, using a pre-trained model on a new dataset without fine-tun…
GPGait: Generalized Pose-based Gait Recognition
Yang Fu, Shibei Meng, Saihui Hou +2
Recent works on pose-based gait recognition have demonstrated the potential of using such simple information to achieve results comparable to silhouette-based methods. However, the…
Exploring Deep Models for Practical Gait Recognition
Chao Fan, Saihui Hou, Yongzhen Huang +1
Gait recognition is a rapidly advancing vision technique for person identification from a distance. Prior studies predominantly employed relatively shallow networks to extract subt…
OpenGait: Revisiting Gait Recognition Toward Better Practicality
Chao Fan, Junhao Liang, Chuanfu Shen +3
Gait recognition is one of the most critical long-distance identification technologies and increasingly gains popularity in both research and industry communities. Despite the sign…
Progressive Feature Learning for Realistic Cloth-Changing Gait Recognition
Xuqian Ren, Saihui Hou, Chunshui Cao +2
Gait recognition is instrumental in crime prevention and social security, for it can be conducted at a long distance to figure out the identity of persons. However, existing datase…
Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark
Chao Fan, Saihui Hou, Jilong Wang +2
Gait depicts individuals' unique and distinguishing walking patterns and has become one of the most promising biometric features for human identification. As a fine-grained recogni…
GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality
Junhao Liang, Chao Fan, Saihui Hou +3
Gait is one of the most promising biometrics to identify individuals at a long distance. Although most previous methods have focused on recognizing the silhouettes, several end-to-…
Probabilistic Contrastive Learning for Domain Adaptation
Junjie Li, Yixin Zhang, Zilei Wang +3
Contrastive learning has shown impressive success in enhancing feature discriminability for various visual tasks in a self-supervised manner, but the standard contrastive paradigm…
Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes
Yunjie Peng, Kang Ma, Yang Zhang +1
Gait recognition captures gait patterns from the walking sequence of an individual for identification. Most existing gait recognition methods learn features from silhouettes or ske…
Deeply Exploit Depth Information for Object Detection
Saihui Hou, Zilei Wang, Feng Wu
This paper addresses the issue on how to more effectively coordinate the depth with RGB aiming at boosting the performance of RGB-D object detection. Particularly, we investigate t…