158 citations · 716 across the 49 of their papers we have counts for
29 papers · 1 filter
Any-to-Bokeh: Arbitrary-Subject Video Refocusing with Video Diffusion Model
Yang Yang, Siming Zheng, Qirui Yang +6
Diffusion models have recently emerged as powerful tools for camera simulation, enabling both geometric transformations and realistic optical effects. Among these, image-based boke…
A Study of Unsupervised Evaluation Metrics for Practical and Automatic Domain Adaptation
Minghao Chen, Zepeng Gao, Shuai Zhao +4
Unsupervised domain adaptation (UDA) methods facilitate the transfer of models to target domains without labels. However, these methods necessitate a labeled target validation set…
PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer
Honghui Yang, Wenxiao Wang, Minghao Chen +5
Recent Transformer-based 3D object detectors learn point cloud features either from point- or voxel-based representations. However, the former requires time-consuming sampling whil…
General Rotation Invariance Learning for Point Clouds via Weight-Feature Alignment
Liang Xie, Yibo Yang, Wenxiao Wang +4
Compared to 2D images, 3D point clouds are much more sensitive to rotations. We expect the point features describing certain patterns to keep invariant to the rotation transformati…
CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation
Yuqi Lin, Minghao Chen, Wenxiao Wang +5
Weakly supervised semantic segmentation (WSSS) with image-level labels is a challenging task. Mainstream approaches follow a multi-stage framework and suffer from high training cos…
GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds
Honghui Yang, Tong He, Jiaheng Liu +5
Despite the tremendous progress of Masked Autoencoders (MAE) in developing vision tasks such as image and video, exploring MAE in large-scale 3D point clouds remains challenging du…
PriorLane: A Prior Knowledge Enhanced Lane Detection Approach Based on Transformer
Qibo Qiu, Haiming Gao, Wei Hua +2
Lane detection is one of the fundamental modules in self-driving. In this paper we employ a transformer-only method for lane detection, thus it could benefit from the blooming deve…
Towards In-distribution Compatibility in Out-of-distribution Detection
Boxi Wu, Jie Jiang, Haidong Ren +7
Deep neural network, despite its remarkable capability of discriminating targeted in-distribution samples, shows poor performance on detecting anomalous out-of-distribution data. T…
Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph
Honghui Yang, Zili Liu, Xiaopei Wu +4
Two-stage detectors have gained much popularity in 3D object detection. Most two-stage 3D detectors utilize grid points, voxel grids, or sampled keypoints for RoI feature extractio…
Motion-aware Memory Network for Fast Video Salient Object Detection
Xing Zhao, Haoran Liang, Peipei Li +4
Previous methods based on 3DCNN, convLSTM, or optical flow have achieved great success in video salient object detection (VSOD). However, they still suffer from high computational…
Towards Efficient Adversarial Training on Vision Transformers
Boxi Wu, Jindong Gu, Zhifeng Li +3
Vision Transformer (ViT), as a powerful alternative to Convolutional Neural Network (CNN), has received much attention. Recent work showed that ViTs are also vulnerable to adversar…
CLRNet: Cross Layer Refinement Network for Lane Detection
Tu Zheng, Yifei Huang, Yang Liu +4
Lane is critical in the vision navigation system of the intelligent vehicle. Naturally, lane is a traffic sign with high-level semantics, whereas it owns the specific local pattern…
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection
Liang Peng, Senbo Yan, Boxi Wu +3
Monocular 3D object detection is one of the most challenging tasks in 3D scene understanding. Due to the ill-posed nature of monocular imagery, existing monocular 3D detection meth…
VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and Adaptation
Jiong Wang, Zhou Zhao, Weike Jin +5
For face presentation attack detection (PAD), most of the spoofing cues are subtle, local image patterns (e.g., local image distortion, 3D mask edge and cut photo edges). The repre…
SimulSLT: End-to-End Simultaneous Sign Language Translation
Aoxiong Yin, Zhou Zhao, Jinglin Liu +4
Sign language translation as a kind of technology with profound social significance has attracted growing researchers' interest in recent years. However, the existing sign language…
SimulLR: Simultaneous Lip Reading Transducer with Attention-Guided Adaptive Memory
Zhijie Lin, Zhou Zhao, Haoyuan Li +4
Lip reading, aiming to recognize spoken sentences according to the given video of lip movements without relying on the audio stream, has attracted great interest due to its applica…
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention
Wenxiao Wang, Lu Yao, Long Chen +4
Transformers have made great progress in dealing with computer vision tasks. However, existing vision transformers do not yet possess the ability of building the interactions among…
Salient Object Ranking with Position-Preserved Attention
Hao Fang, Daoxin Zhang, Yi Zhang +5
Instance segmentation can detect where the objects are in an image, but hard to understand the relationship between them. We pay attention to a typical relationship, relative salie…
Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
Yang Liu, Weifeng Zhang, Chao Xiang +3
Few-shot learning (FSL) aims to learn a classifier that can be easily adapted to accommodate new tasks not seen during training, given only a few examples. To handle the limited-da…
Discriminative-Generative Dual Memory Video Anomaly Detection
Xin Guo, Zhongming Jin, Chong Chen +5
Recently, people tried to use a few anomalies for video anomaly detection (VAD) instead of only normal data during the training process. A side effect of data imbalance occurs when…
OCM3D: Object-Centric Monocular 3D Object Detection
Liang Peng, Fei Liu, Senbo Yan +2
Image-only and pseudo-LiDAR representations are commonly used for monocular 3D object detection. However, methods based on them have shortcomings of either not well capturing the s…
X-view: Non-egocentric Multi-View 3D Object Detector
Liang Xie, Guodong Xu, Deng Cai +1
3D object detection algorithms for autonomous driving reason about 3D obstacles either from 3D birds-eye view or perspective view or both. Recent works attempt to improve the detec…
ES-Net: Erasing Salient Parts to Learn More in Re-Identification
Dong Shen, Shuai Zhao, Jinming Hu +3
As an instance-level recognition problem, re-identification (re-ID) requires models to capture diverse features. However, with continuous training, re-ID models pay more and more a…
DMN4: Few-shot Learning via Discriminative Mutual Nearest Neighbor Neural Network
Yang Liu, Tu Zheng, Jie Song +2
Few-shot learning (FSL) aims to classify images under low-data regimes, where the conventional pooled global feature is likely to lose useful local characteristics. Recent work has…