activity
20162026
most citedSoftTriple Loss: Deep Metric Learning Without Triplet Sampling

92 citations · 291 across the 39 of their papers we have counts for

collaborators

39 papers

cs.CV2026

FusionBERT: Multi-View Image--3D Retrieval via Cross-Attention Visual Fusion and Normal-Aware 3D Encoder

Wei Li, Yufan Ren, Hanqing Jiang +6

We propose FusionBERT, a novel multi-view visual fusion framework for image--3D multimodal retrieval. Existing image--3D representation learning methods predominantly focus on feat…

cs.CV2026

Revisiting Cross-Attention Mechanisms: Leveraging Beneficial Noise for Domain-Adaptive Learning

Zelin Zang, Yehui Yang, Fei Wang +2

Unsupervised Domain Adaptation (UDA) seeks to transfer knowledge from a labeled source domain to an unlabeled target domain but often suffers from severe domain and scale gaps that…

cs.CV2024

FaceChain-FACT: Face Adapter with Decoupled Training for Identity-preserved Personalization

Cheng Yu, Haoyu Xie, Lei Shang +4

In the field of human-centric personalized image generation, the adapter-based method obtains the ability to customize and generate portraits by text-to-image training on facial da…

cs.CV2024

ControLRM: Fast and Controllable 3D Generation via Large Reconstruction Model

Hongbin Xu, Weitao Chen, Zhipeng Zhou +4

Despite recent advancements in 3D generation methods, achieving controllability still remains a challenging issue. Current approaches utilizing score-distillation sampling are hind…

cs.CV2024

Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning

Siyuan Li, Juanxi Tian, Zedong Wang +6

This paper delves into the interplay between vision backbones and optimizers, unvealing an inter-dependent phenomenon termed \textit{\textbf{b}ackbone-\textbf{o}ptimizer \textbf{c}…

cs.CV2024★ 3 cited

TopoFR: A Closer Look at Topology Alignment on Face Recognition

Jun Dan, Yang Liu, Jiankang Deng +4

The field of face recognition (FR) has undergone significant advancements with the rise of deep learning. Recently, the success of unsupervised learning and graph neural networks h…

cs.CV2024

RobustMVS: Single Domain Generalized Deep Multi-view Stereo

Hongbin Xu, Weitao Chen, Baigui Sun +2

Despite the impressive performance of Multi-view Stereo (MVS) approaches given plenty of training samples, the performance degradation when generalizing to unseen domains has not b…

cs.LG2024

Dataset Growth

Ziheng Qin, Zhaopan Xu, Yukun Zhou +10

Deep learning benefits from the growing abundance of available data. Meanwhile, efficiently dealing with the growing data scale has become a challenge. Data publicly available are…

cs.CV2024

TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On

Jiazheng Xing, Chao Xu, Yijie Qian +5

Virtual try-on focuses on adjusting the given clothes to fit a specific person seamlessly while avoiding any distortion of the patterns and textures of the garment. However, the cl…

cs.CV2024

FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio

Chao Xu, Yang Liu, Jiazheng Xing +8

In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and I…

cs.CV2024

Beyond Talking -- Generating Holistic 3D Human Dyadic Motion for Communication

Mingze Sun, Chao Xu, Xinyu Jiang +3

In this paper, we introduce an innovative task focused on human communication, aiming to generate 3D holistic human motions for both speakers and listeners. Central to our approach…

cs.CV2024

StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fields

Hongbin Xu, Weitao Chen, Feng Xiao +2

4D style transfer aims at transferring arbitrary visual style to the synthesized novel views of a dynamic 4D scene with varying viewpoints and times. Existing efforts on 3D style t…

cs.CV2024

FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation

Pengchong Qiao, Lei Shang, Chang Liu +3

Subject-driven generation has garnered significant interest recently due to its ability to personalize text-to-image generation. Typical works focus on learning the new subject's p…

cs.CV2024

PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation

Haoyu Xie, Changqi Wang, Jian Zhao +4

Tremendous breakthroughs have been developed in Semi-Supervised Semantic Segmentation (S4) through contrastive learning. However, due to limited annotations, the guidance on unlabe…

cs.LG2024★ 3 cited

Switch EMA: A Free Lunch for Better Flatness and Sharpness

Siyuan Li, Zicheng Liu, Juanxi Tian +9

Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DN…

cs.CV2024★ 7 cited

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond

Siyuan Li, Luyuan Zhang, Zedong Wang +8

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and…

cs.LG2023★ 1 cited

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning

Hongyu Zang, Xin Li, Leiji Zhang +5

While bisimulation-based approaches hold promise for learning robust state representations for Reinforcement Learning (RL) tasks, their efficacy in offline RL tasks has not been up…

cs.CV2023

FaceChain: A Playground for Human-centric Artificial Intelligence Generated Content

Yang Liu, Cheng Yu, Lei Shang +17

Recent advancement in personalized image generation have unveiled the intriguing capability of pre-trained text-to-image models on learning identity information from a collection o…

cs.CV2023★ 2 cited

TransFace++: Rethinking the Face Recognition Paradigm with a Focus on Accuracy, Efficiency, and Security

Jun Dan, Yang Liu, Baigui Sun +2

Face Recognition (FR) technology has made significant strides with the emergence of deep learning. Typically, most existing FR models are built upon Convolutional Neural Networks (…

cs.CV2023★ 1 cited

CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo

Weitao Chen, Hongbin Xu, Zhipeng Zhou +4

The core of Multi-view Stereo(MVS) is the matching process among reference and source pixels. Cost aggregation plays a significant role in this process, while previous methods focu…

cs.CV2023★ 2 cited

The 3rd Anti-UAV Workshop & Challenge: Methods and Results

Jian Zhao, Jianan Li, Lei Jin +20

The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UA…

cs.CV2023★ 1 cited

PointDC:Unsupervised Semantic Segmentation of 3D Point Clouds via Cross-modal Distillation and Super-Voxel Clustering

Zisheng Chen, Hongbin Xu, Weitao Chen +5

Semantic segmentation of point clouds usually requires exhausting efforts of human annotations, hence it attracts wide attention to the challenging topic of learning from unlabeled…

cs.CV2022★ 1 cited

Improving Training and Inference of Face Recognition Models via Random Temperature Scaling

Lei Shang, Mouxiao Huang, Wu Shi +6

Data uncertainty is commonly observed in the images for face recognition (FR). However, deep learning algorithms often make predictions with high confidence even for uncertain or i…

cs.LG2022★ 3 cited

EVNet: An Explainable Deep Network for Dimension Reduction

Zelin Zang, Shenghui Cheng, Linyan Lu +7

Dimension reduction (DR) is commonly utilized to capture the intrinsic structure and transform high-dimensional data into low-dimensional space while retaining meaningful propertie…