Search Results for author:
Found 15 papers, 4 papers with code
Predicting Human Activities Using Stochastic Grammar
This paper presents a novel method to predict future human activities from partially observed RGB-D videos.
Monocular 3D Human Pose Estimation by Predicting Depth on Joints
This paper aims at estimating full-body 3D human poses from monocular images of which the biggest challenge is the inherent ambiguity introduced by lifting the 2D pose into 3D space.
Ranked #113 on
3D Human Pose Estimation
on Human3.6M
(PA-MPJPE metric)
Jointly Recognizing Object Fluents and Tasks in Egocentric Videos
Given an egocentric video, a beam search algorithm is applied to jointly recognizing the object fluents in each frame, and the task of the entire video.
Inferring Shared Attention in Social Scene Videos
We collect a new dataset VideoCoAtt from public TV show videos, containing 380 complex video sequences with more than 492, 000 frames that include diverse social scenes for shared attention study.
Where and Why Are They Looking? Jointly Inferring Human Attention and Intentions in Complex Tasks
We built a new video dataset of tasks, intentions, and attention.
Inverse Discriminative Networks for Handwritten Signature Verification
We test our method on the Chinese signature dataset and other three signature datasets of different languages: CEDAR, BHSig-B, and BHSig-H.
Multi-sensor joint target detection, tracking and classification via Bernoulli filter
This paper focuses on \textit{joint detection, tracking and classification} (JDTC) of a target via multi-sensor fusion.
Generative Steganography Network
A new steganographic approach called generative steganography (GS) has emerged recently, in which stego images (images containing secret data) are generated from secret data directly without cover media.
Inverse Compositional Learning for Weakly-supervised Relation Grounding
In this study, we introduce a novel approach called inverse compositional learning (ICL) for weakly-supervised video relation grounding.
IntentQA: Context-aware Video Intent Reasoning
In this paper, we propose a novel task IntentQA, a special VideoQA task focusing on video intent reasoning, which has become increasingly important for AI with its advantages in equipping AI agents with the capability of reasoning beyond mere recognition in daily tasks.
Generative Steganography Diffusion
However, existing GAN-based GS methods cannot completely recover the hidden secret data due to the lack of network invertibility, while Flow-based methods produce poor image quality due to the stringent reversibility restriction in each module.
Generative Steganographic Flow
In the forward mapping, secret data is hidden in the input latent of Glow model to generate stego images.
Efficient Monaural Speech Enhancement using Spectrum Attention Fusion
Speech enhancement is a demanding task in automated speech processing pipelines, focusing on separating clean speech from noisy channels.
Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement
DETR-like methods have significantly increased detection performance in an end-to-end manner.
Ranked #2 on
Object Detection
on COCO 2017 val
Task-Driven Exploration: Decoupling and Inter-Task Feedback for Joint Moment Retrieval and Highlight Detection
Video moment retrieval and highlight detection are two highly valuable tasks in video understanding, but until recently they have been jointly studied.
