128 citations · 932 across the 39 of their papers we have counts for
39 papers · 1 filter
LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
Zhenfei Yin, Jiong Wang, Jianjian Cao +9
Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the developme…
Latent Distribution Adjusting for Face Anti-Spoofing
Qinghong Sun, Zhenfei Yin, Yichao Wu +2
With the development of deep learning, the field of face anti-spoofing (FAS) has witnessed great progress. FAS is usually considered a classification problem, where each class is a…
Siamese DETR
Zeren Chen, Gengshi Huang, Wei Li +5
Recent self-supervised methods are mainly designed for representation learning with the base model, e.g., ResNets or ViTs. They cannot be easily transferred to DETR, with task-spec…
Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline
Yangguang Li, Bin Huang, Zeren Chen +8
Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more and more attention, and BEV representation is promising as the foundation for next-generation…
PalGAN: Image Colorization with Palette Generative Adversarial Networks
Yi Wang, Menghan Xia, Lu Qi +2
Multimodal ambiguity and color bleeding remain challenging in colorization. To tackle these problems, we propose a new GAN-based colorization approach PalGAN, integrated with palet…
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning
Junting Pan, Ziyi Lin, Xiatian Zhu +2
Capitalizing on large pre-trained models for various downstream tasks of interest have recently emerged with promising performance. Due to the ever-growing model size, the standard…
X-Learner: Learning Cross Sources and Tasks for Universal Visual Representation
Yinan He, Gengshi Huang, Siyu Chen +7
In computer vision, pre-training models based on largescale supervised learning have been proven effective over the past few years. However, existing works mostly focus on learning…
Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision
Yufeng Cui, Lichen Zhao, Feng Liang +2
Contrastive Language-Image Pretraining (CLIP) has emerged as a novel paradigm to learn visual models from language supervision. While researchers continue to push the frontier of C…
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy
Yuanhan Zhang, Qinghong Sun, Yichun Zhou +7
Large-scale datasets play a vital role in computer vision. But current datasets are annotated blindly without differentiation to samples, making the data collection inefficient and…
RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training
Luya Wang, Feng Liang, Yangguang Li +3
Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability. However, the dominant method, contrastive…
ForgeryNet -- Face Forgery Analysis Challenge 2021: Methods and Results
Yinan He, Lu Sheng, Jing Shao +19
The rapid progress of photorealistic synthesis techniques has reached a critical point where the boundary between real and manipulated images starts to blur. Recently, a mega-scale…
A Simple Long-Tailed Recognition Baseline via Vision-Language Model
Teli Ma, Shijie Geng, Mengmeng Wang +5
The visual world naturally exhibits a long-tailed distribution of open classes, which poses great challenges to modern visual systems. Existing approaches either perform class re-b…
INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li +24
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However,…
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm
Yangguang Li, Feng Liang, Lichen Zhao +5
Recently, large-scale Contrastive Language-Image Pre-training (CLIP) has attracted unprecedented attention for its impressive zero-shot recognition ability and excellent transferab…
Few-Shot Domain Expansion for Face Anti-Spoofing
Bowen Yang, Jing Zhang, Zhenfei Yin +1
Face anti-spoofing (FAS) is an indispensable and widely used module in face recognition systems. Although high accuracy has been achieved, a FAS system will never be perfect due to…
ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis
Yinan He, Bei Gan, Siyu Chen +6
The rapid progress of photorealistic synthesis techniques has reached at a critical point where the boundary between real and manipulated images starts to blur. Thus, benchmarking…
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
Yuanhan Zhang, Zhenfei Yin, Jing Shao +22
As facial interaction systems are prevalently deployed, security and reliability of these systems become a critical issue, with substantial research efforts devoted. Among them, fa…
PV-NAS: Practical Neural Architecture Search for Video Recognition
Zihao Wang, Chen Lin, Lu Sheng +2
Recently, deep learning has been utilized to solve video recognition problem due to its prominent representation ability. Deep neural networks for video tasks is highly customized…
Learning Connectivity of Neural Networks from a Topological Perspective
Kun Yuan, Quanquan Li, Jing Shao +1
Seeking effective neural networks is a critical and practical field in deep learning. Besides designing the depth, type of convolution, normalization, and nonlinearities, the topol…
CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations
Yuanhan Zhang, Zhenfei Yin, Yidong Li +4
As facial interaction systems are prevalently deployed, security and reliability of these systems become a critical issue, with substantial research efforts devoted. Among them, fa…
Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues
Yuyang Qian, Guojun Yin, Lu Sheng +2
As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging researc…
1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020
Siyu Chen, Junting Pan, Guanglu Song +6
This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly b…
Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization
Junting Pan, Siyu Chen, Mike Zheng Shou +3
Localizing persons and recognizing their actions from videos is a challenging task towards high-level video understanding. Recent advances have been achieved by modeling direct pai…
Morphing and Sampling Network for Dense Point Cloud Completion
Minghua Liu, Lu Sheng, Sheng Yang +2
3D point cloud completion, the task of inferring the complete geometric shape from a partial point cloud, has been attracting attention in the community. For acquiring high-fidelit…