246 citations · 1.2k across the 71 of their papers we have counts for
19 papers · 1 filter
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen +5
Recent progress has shown that large-scale pre-training using contrastive image-text pairs can be a promising alternative for high-quality visual representation learning from natur…
NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo
Yi Wei, Shaohui Liu, Yongming Rao +3
In this work, we present a new multi-view depth estimation method that utilizes both conventional reconstruction and learning-based priors over the recently proposed neural radianc…
Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization
Jianglin Lu, Hailing Wang, Jie Zhou +2
Recently, deep hashing methods have been widely used in image retrieval task. Most existing deep hashing approaches adopt one-to-one quantization to reduce information loss. Howeve…
Structure-Preserving Image Super-Resolution
Cheng Ma, Yongming Rao, Jiwen Lu +1
Structures matter in single image super-resolution (SISR). Benefiting from generative adversarial networks (GANs), recent studies have promoted the development of SISR by recoverin…
Deep Relational Metric Learning
Wenzhao Zheng, Borui Zhang, Jiwen Lu +1
This paper presents a deep relational metric learning (DRML) framework for image clustering and retrieval. Most existing deep metric learning methods learn an embedding space with…
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
Xumin Yu, Yongming Rao, Ziyi Wang +3
Point clouds captured in real-world applications are often incomplete due to the limited sensor resolution, single viewpoint, and occlusion. Therefore, recovering the complete poin…
Group-aware Contrastive Regression for Action Quality Assessment
Xumin Yu, Yongming Rao, Wenliang Zhao +2
Assessing action quality is challenging due to the subtle differences between videos and large variations in scores. Most existing approaches tackle this problem by regressing a qu…
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection
Yongming Rao, Benlin Liu, Yi Wei +3
3D point cloud understanding has made great progress in recent years. However, one major bottleneck is the scarcity of annotated real datasets, especially compared to 2D object det…
Masked Face Recognition Challenge: The WebFace260M Track Report
Zheng Zhu, Guan Huang, Jiankang Deng +9
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…
Towards Interpretable Deep Metric Learning with Structural Matching
Wenliang Zhao, Yongming Rao, Ziyi Wang +2
How do the neural networks distinguish two images? It is of critical importance to understand the matching mechanism of deep models for developing reliable intelligent systems for…
Person Re-identification via Attention Pyramid
Guangyi Chen, Tianpei Gu, Jiwen Lu +2
In this paper, we propose an attention pyramid method for person re-identification. Unlike conventional attention-based methods which only learn a global attention map, our attenti…
Instance Similarity Learning for Unsupervised Feature Representation
Ziwei Wang, Yunsong Wang, Ziyi Wu +2
In this paper, we propose an instance similarity learning (ISL) method for unsupervised feature representation. Conventional methods assign close instance pairs in the feature spac…
Generalizable Mixed-Precision Quantization via Attribution Rank Preservation
Ziwei Wang, Han Xiao, Jiwen Lu +1
In this paper, we propose a generalizable mixed-precision quantization (GMPQ) method for efficient inference. Conventional methods require the consistency of datasets for bitwidth…
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Yongming Rao, Guangyi Chen, Jiwen Lu +1
Attention mechanism has demonstrated great potential in fine-grained visual recognition tasks. In this paper, we present a counterfactual attention learning method to learn more ef…
Human Trajectory Prediction via Counterfactual Analysis
Guangyi Chen, Junlong Li, Jiwen Lu +1
Forecasting human trajectories in complex dynamic environments plays a critical role in autonomous vehicles and intelligent robots. Most existing methods learn to predict future tr…
Modeling Explicit Concerning States for Reinforcement Learning in Visual Dialogue
Zipeng Xu, Fandong Meng, Xiaojie Wang +3
To encourage AI agents to conduct meaningful Visual Dialogue (VD), the use of Reinforcement Learning has been proven potential. In Reinforcement Learning, it is crucial to represen…
Temporal Modeling Approaches for Large-scale Youtube-8M Video Understanding
Fu Li, Chuang Gan, Xiao Liu +6
This paper describes our solution for the video recognition task of the Google Cloud and YouTube-8M Video Understanding Challenge that ranked the 3rd place. Because the challenge p…
Nonlinear Local Metric Learning for Person Re-identification
Siyuan Huang, Jiwen Lu, Jie Zhou +1
Person re-identification aims at matching pedestrians observed from non-overlapping camera views. Feature descriptor and metric learning are two significant problems in person re-i…
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question Answering
Haoyuan Gao, Junhua Mao, Jie Zhou +3
In this paper, we present the mQA model, which is able to answer questions about the content of an image. The answer can be a sentence, a phrase or a single word. Our model contain…