Search Results for author:
Found 18 papers, 5 papers with code
ProS: Facial Omni-Representation Learning via Prototype-based Self-Distillation
This paper presents a novel approach, called Prototype-based Self-Distillation (ProS), for unsupervised face representation learning.
Transform-Equivariant Consistency Learning for Temporal Sentence Grounding
This paper addresses the temporal sentence grounding (TSG).
Hypotheses Tree Building for One-Shot Temporal Sentence Localization
Given an untrimmed video, temporal sentence localization (TSL) aims to localize a specific segment according to a given sentence query.
Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding
All existing works first utilize a sparse sampling strategy to extract a fixed number of video frames and then conduct multi-modal interactions with query sentence for reasoning.
MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
The vision of this paper is to provide a more comprehensive and practical benchmark study for MIG in order to eliminate the need for tedious manual benchmarking and tuning efforts.
Backdoor Attacks on Crowd Counting
In this paper, we propose two novel Density Manipulation Backdoor Attacks (DMBA$^{-}$ and DMBA$^{+}$) to attack the model to produce arbitrarily large or small density estimations.
Unsupervised Temporal Video Grounding with Deep Semantic Clustering
Temporal video grounding (TVG) aims to localize a target segment in a video according to a given sentence query.
Memory-Guided Semantic Learning Network for Temporal Sentence Grounding
To tackle this issue, we propose a memory-augmented network, called Memory-Guided Semantic Learning Network (MGSL-Net), that learns and memorizes the rarely appeared content in TSG tasks.
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search
Lymph node station (LNS) delineation from computed tomography (CT) scans is an indispensable step in radiation oncology workflow.
Heterogeneous Face Frontalization via Domain Agnostic Learning
We propose a domain agnostic learning-based generative adversarial network (DAL-GAN) which can synthesize frontal views in the visible domain from thermal faces with pose variations.
Multimodal Face Synthesis from Visual Attributes
Extensive experiments and comparisons with several state-of-the-art methods are performed to verify the effectiveness of the proposed attribute-based multimodal synthesis method.
A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset
Thermal face imagery, which captures the naturally emitted heat from the face, is limited in availability compared to face imagery in the visible spectrum.
Multi-Scale Thermal to Visible Face Verification via Attribute Guided Synthesis
Finally, a pre-trained VGG-Face network is leveraged to extract features from the synthesized image and the input visible image for verification.
Facial Synthesis from Visual Attributes via Sketch using Multi-Scale Generators
In this paper, we take a different approach, where we formulate the original problem as a stage-wise learning problem.
Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis
Polarimetric thermal to visible face verification entails matching two images that contain significant domain differences.
Polarimetric Thermal to Visible Face Verification via Attribute Preserved Synthesis
A pre-trained VGG-Face network is used to extract the attributes from the visible image.
Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs
In this paper, we take a different approach, where we formulate the original problem as a stage-wise learning problem.
GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks
The primary aim of this work is to demonstrate that information preserved by landmarks (gender in particular) can be further accentuated by leveraging generative models to synthesize corresponding faces.
