Search Results for author:
Found 19 papers, 7 papers with code
Mining the Benefits of Two-stage and One-stage HOI Detection
To this end, we propose a novel one-stage framework with disentangling human-object detection and interaction classification in a cascade manner.
Ranked #7 on
Human-Object Interaction Detection
on V-COCO
Weakly Supervised High-Fidelity Clothing Model Generation
The development of online economics arouses the demand of generating images of models on product clothes, to display new clothes and promote sales.
Ranked #2 on
Virtual Try-on
on MPV
GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection
In this paper, we reveal and address the disadvantages of the conventional query-driven HOI detectors from the two aspects.
Ranked #12 on
Human-Object Interaction Detection
on HICO-DET
Towards 3D Face Reconstruction in Perspective Projection: Estimating 6DoF Face Pose from Monocular Image
In 3D face reconstruction, orthogonal projection has been widely employed to substitute perspective projection to simplify the fitting process.
ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022
In this report, we present the ReLER@ZJU-Alibaba submission to the Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2022.
Ranked #3 on
Natural Language Queries
on Ego4D
Masked Contrastive Pre-Training for Efficient Video-Text Retrieval
Our MAC aims to reduce video representation's spatial and temporal redundancy in the VidLP model by a mask sampling mechanism to improve pre-training efficiency.
Ranked #37 on
Video Retrieval
on MSR-VTT-1kA
(using extra training data)
CAMP-Net: Consistency-Aware Multi-Prior Network for Accelerated MRI Reconstruction
To maximize the benefits of image domain and k-domain prior knowledge, the reconstructions are aggregated in a frequency fusion module, exploiting their complementary properties to optimize the trade-off between artifact removal and fine detail preservation.
Augmented Bi-path Network for Few-shot Learning
Finally, the model learns to compare global and local features separately, i. e., in two paths, before merging the similarities.
Pixel-Face: A Large-Scale, High-Resolution Benchmark for 3D Face Reconstruction
It is also a challenging task due to the lack of high-quality datasets that can fuel current deep learning-based methods.
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020.
A Dual-Critic Reinforcement Learning Framework for Frame-level Bit Allocation in HEVC/H.265
This paper introduces a dual-critic reinforcement learning (RL) framework to address the problem of frame-level bit allocation in HEVC/H. 265.
Multi-Granularity Network with Modal Attention for Dense Affective Understanding
Video affective understanding, which aims to predict the evoked expressions by the video content, is desired for video creation and recommendation.
A Unified Review of Deep Learning for Automated Medical Coding
Automated medical coding, an essential task for healthcare operation and delivery, makes unstructured data manageable by predicting medical codes from clinical documents.
A Contrastive Framework for Learning Sentence Representations from Pairwise and Triple-wise Perspective in Angular Space
Learning high-quality sentence representations is a fundamental problem of natural language processing which could benefit a wide range of downstream tasks.
Context Attention Network for Skeleton Extraction
Skeleton extraction is a task focused on providing a simple representation of an object by extracting the skeleton from the given binary or RGB image.
A Nonparametric Approach with Marginals for Modeling Consumer Choice
The marginal distribution model (MDM) is one such model, that requires only the specification of marginal distributions of the random utilities.
Quality-Constant Per-Shot Encoding by Two-Pass Learning-based Rate Factor Prediction
With the help of first pass predicted RF and corresponding actual quality as feedback, the second pass prediction will be highly accurate.
GANHead: Towards Generative Animatable Neural Head Avatars
To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars.
CSST Strong Lensing Preparation: a Framework for Detecting Strong Lenses in the Multi-color Imaging Survey by the China Survey Space Telescope (CSST)
To overcome these challenges, we have developed a framework based on a hierarchical visual Transformer with a sliding window technique to search for strong lensing systems within entire images.
