Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileAcademic lineage
Possible advisorsa guess from early papers, not confirmed
- King Ngi NganSuggested from co-authorship
Is this you? Claim this profile to confirm or dismiss it.
Works70 from public data
- Thinking in Frequency: Face Forgery Detection by Mining Frequency-Aware Clues1,284
This work proposes a novel Frequency in Face Forgery Network (F3-Net), taking advantages of two different but complementary frequency-aware clues, and applies DCT as the applied frequency-domain transformation to introduce frequency into the face forgery detection.
- HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis567
A new attentionbased deep neural network, named as HydraPlus-Net (HPnet), that multi-directionally feeds the multi-level attention maps to different feature layers to enrich the final feature representations for a pedestrian image.
- Morphing and Sampling Network for Dense Point Cloud Completion384
This work proposes a novel approach to complete the partial point cloud in two stages, which outperforms the existing methods in both the Earth Mover's Distance (EMD) and the Chamfer Distance (CD).
- GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving361
This work leverages the off-the-shelf 2D object detector to efficiently obtain a coarse cuboid for each predicted 2D box and explores the 3D structure information of the object by employing the visual features of visible surfaces.
- CAMP: Cross-Modal Adaptive Message Passing for Text-Image Retrieval361
This paper proposes Cross-modal Adaptive Message Passing (CAMP), which adaptively controls the information flow for message passing across modalities and properly handles negative pairs and irrelevant information with an adaptive gating scheme.
- Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition343
A novel compact motion representation for video action recognition, named Optical Flow guided Feature (OFF), which enables the network to distill temporal information through a fast and robust approach and is complementary to other motion modalities such as optical flow.
- Avatar-Net: Multi-scale Zero-Shot Style Transfer by Feature Decoration328
This paper proposes an efficient yet effective Avatar-Net that enables visually plausible multi-scale transfer for arbitrary style in real-time and demonstrates the state-of-the-art effectiveness and efficiency of the proposed method in generating high-quality stylized images.
- 261
- ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis234
The ForgeryNet dataset is constructed, an extremely large face forgery dataset with unified annotations in image- and video-level data across four tasks, and it is hoped that the scale, quality, and variety of this dataset will foster further research and innovation in the area of face forgeries classification, as well as spatial and temporal forgery localization etc.
- Semantics Disentangling for Text-To-Image Generation210
A novel photo-realistic text-to-image generation model that implicitly disentangles semantics to both fulfill the high- level semantic consistency and low-level semantic diversity and a visual-semantic embedding strategy by semantic-conditioned batch normalization to find diverse low- level semantics.
- DanceFormer: Music Conditioned 3D Dance Generation with Parametric Motion Transformer204
Extensive experiments demonstrate that the proposed DanceFormer, even trained by existing datasets, can generate fluent, performative, and music-matched 3D dances that surpass previous works quantitatively and qualitatively.
- Exploring Disentangled Feature Representation Beyond Face Identification163
Comprehensive evaluations demonstrate that the proposed features not only preserve state-of-the-art identity verification performance on LFW, but also acquire comparable discriminative power for face attribute recognition on CelebA and LFWA.
- Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition160
This work presents two new pooling cells to encourage feature interactions, and sheds light on how one could resolve ambiguous and noisy object and predicate annotations by Intra-Hierarchical trees (IH-tree).
- Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific Localization154
A flexible Attribute Localization Module (ALM) is proposed to adaptively discover the most discriminative regions and learns the regional features for each attribute at multiple levels and a feature pyramid architecture is introduced to enhance the attribute-specific localization at low-levels with high-level semantic guidance.
- 144
- 140
- Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds131
This work introduces a new 3D object detection method, named as Back-tracing Representative Points Network (BRNet), which generatively back-traces the representative points from the vote centers and also revisits complementary seed points around these generated points, so as to better capture the fine local structural features surrounding the potential objects from the raw point clouds.
- Diffusion Model is Secretly a Training-Free Open Vocabulary Semantic Segmenter115
The potential of generative text-to-image diffusion models as highly efficient open-vocabulary semantic segmenters are uncovered, and a novel training-free approach named DiffSegmenter is introduced that achieves impressive results for open-vocabulary semantic segmentation.
- Video Generation From Single Semantic Label Map111
A cVAE for predicting optical flow is employed as a beneficial intermediate step to generate a video sequence conditioned on the initial single frame, and a semantic label map is integrated into the flow prediction module to achieve major improvements in the image-to-video generation process.
- Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline100
This paper proposes a simple yet effective framework, termed Fast-BEV, which is capable of performing faster BEV perception on the on-vehicle chips of autonomous driving, and introduces a strong data augmentation strategy for both image and BEV space to avoid over-fitting.
- Context and Attribute Grounded Dense Captioning83
This work designs a novel end-to-end context and attribute grounded dense captioning framework consisting of a contextual visual mining module and a multi-level attribute grounded description generation module that incorporates an auxiliary supervision from hierarchical linguistic attributes to augment the distinctiveness of the learned captions.
- 70
- T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation59
This work evaluates 15 prominent diffusion models on T2ISafety and reveals several concerns including persistent issues with racial fairness, a tendency to generate toxic content, and significant variation in privacy protection across the models, even with defense methods like concept erasing.
- Toward Explainable 3D Grounded Visual Question Answering: A New Benchmark and Strong Baseline49
This work formally define and address a 3D grounded question answering (GQA) task by collecting a new 3D VQA dataset, referred to as flexible and explainable 3D GQA (FE-3DGQ a), with diverse and relatively free-form question-answer pairs, as well as dense and completely grounded bounding box annotations.
- 44
Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.