172 citations · 1.6k across the 57 of their papers we have counts for
11 papers · 1 filter
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
Liang Pan, Tong Wu, Zhongang Cai +26
As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem f…
PointCLIP: Point Cloud Understanding by CLIP
Renrui Zhang, Ziyu Guo, Wei Zhang +6
Recently, zero-shot and few-shot learning via Contrastive Vision-Language Pre-training (CLIP) have shown inspirational performance on 2D visual recognition, which learns to match i…
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…
Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
Renrui Zhang, Rongyao Fang, Wei Zhang +5
Contrastive Vision-Language Pre-training, known as CLIP, has provided a new paradigm for learning visual representations by using large-scale contrastive image-text pairs. It shows…
Audio-Visual Scene-Aware Dialog and Reasoning using Audio-Visual Transformers with Joint Student-Teacher Learning
Ankit P. Shah, Shijie Geng, Peng Gao +5
In previous work, we have proposed the Audio-Visual Scene-Aware Dialog (AVSD) task, collected an AVSD dataset, developed AVSD technologies, and hosted an AVSD challenge track at bo…
CLIP-Adapter: Better Vision-Language Models with Feature Adapters
Peng Gao, Shijie Geng, Renrui Zhang +5
Large-scale contrastive vision-language pre-training has shown significant progress in visual representation learning. Unlike traditional visual systems trained by a fixed set of d…
Fast Convergence of DETR with Spatially Modulated Co-Attention
Peng Gao, Minghang Zheng, Xiaogang Wang +2
The recently proposed Detection Transformer (DETR) model successfully applies Transformer to objects detection and achieves comparable performance with two-stage object detection f…
Scalable Transformers for Neural Machine Translation
Peng Gao, Shijie Geng, Yu Qiao +3
Transformer has been widely adopted in Neural Machine Translation (NMT) because of its large capacity and parallel training of sequence generation. However, the deployment of Trans…
Gradient Regularized Contrastive Learning for Continual Domain Adaptation
Shixiang Tang, Peng Su, Dapeng Chen +1
Human beings can quickly adapt to environmental changes by leveraging learning experience. However, adapting deep neural networks to dynamic environments by machine learning algori…
RomeBERT: Robust Training of Multi-Exit BERT
Shijie Geng, Peng Gao, Zuohui Fu +1
BERT has achieved superior performances on Natural Language Understanding (NLU) tasks. However, BERT possesses a large number of parameters and demands certain resources to deploy.…
Fast Convergence of DETR with Spatially Modulated Co-Attention
Peng Gao, Minghang Zheng, Xiaogang Wang +2
The recently proposed Detection Transformer (DETR) model successfully applies Transformer to objects detection and achieves comparable performance with two-stage object detection f…