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Frustum PointNets for 3D Object Detection from RGB-D Data
- C. Qi, W. Liu, Chenxia Wu, Hao Su, L. Guibas
- Computer ScienceIEEE/CVF Conference on Computer Vision and…
- 22 November 2017
This work directly operates on raw point clouds by popping up RGBD scans and leverages both mature 2D object detectors and advanced 3D deep learning for object localization, achieving efficiency as well as high recall for even small objects.
Semi-Supervised Nonlinear Hashing Using Bootstrap Sequential Projection Learning
- Chenxia Wu, Jianke Zhu, Deng Cai, Chun Chen, Jiajun Bu
- Computer ScienceIEEE Transactions on Knowledge and Data…
- 1 June 2013
This paper proposes a semi-supervised nonlinear hashing algorithm using bootstrap sequential projection learning which effectively corrects the errors by taking into account of all the previous learned bits holistically without incurring the extra computational overhead.
Watch-n-patch: Unsupervised understanding of actions and relations
- Chenxia Wu, Jiemi Zhang, S. Savarese, Ashutosh Saxena
- Computer ScienceIEEE Conference on Computer Vision and Pattern…
- 7 June 2015
The model learns the high-level action co-occurrence and temporal relations between the actions in the activity video and is applied to unsupervised action segmentation and recognition, and also to a novel application that detects forgotten actions, which is called action patching.
Unsupervised face-name association via commute distance
A novel framework named face- name association via commute distance (FACD), which judges face-name and face-null assignments under a unified framework via commutedistance (CD) algorithm, and a novel anchor-based commute Distance (ACD) algorithm whose main idea is using the anchor point representation structure to accelerate the eigen-decomposition of the adjacency matrix of a graph.
A content-based video copy detection method with randomly projected binary features
- Chenxia Wu, Jianke Zhu, Jiemi Zhang
- Computer Science, EngineeringIEEE Computer Society Conference on Computer…
- 16 June 2012
A keyframe-based copy retrieval method that exhaustively searches the copy candidates from the large video database without indexing and an effective scoring and localization algorithm is proposed to further refine the retrieved copies and accurately locate the video segments.
Watch-n-Patch: Unsupervised Learning of Actions and Relations
- Chenxia Wu, Jiemi Zhang, Ozan Sener, B. Selman, S. Savarese, Ashutosh Saxena
- Computer ScienceIEEE Transactions on Pattern Analysis and Machine…
- 11 March 2016
This work proposes a new probabilistic model that allows for long-range action relations that commonly exist in the composite activities, which is challenging in previous works.
Hierarchical Semantic Labeling for Task-Relevant RGB-D Perception
This work presents an algorithm that produces hierarchical labelings of a scene, following is-part-of and is-type-of relationships, based on a Conditional Random Field that relates pixel-wise and pair-wise observations to labels.
Exploiting Location-Based Context for POI Recommendation When Traveling to a New Region
This research presented New Place Recommendation Algorithm (N-PRA) which is designed based on Latent Factor model, and experimental results show that the algorithm presented in this paper could achieve a better accuracy.
A Convolutional Treelets Binary Feature Approach to Fast Keypoint Recognition
This work directly formulate the keypoint recognition as an image patch retrieval problem, which enjoys the merit of finding the matched keypoint and its pose simultaneously, and proposes a novel convolutional treelets approach to effectively extract the binary features from the patches.