Search Results for author:
Found 20 papers, 14 papers with code
GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval
Current PRVR methods adopt scanning-based clip construction to achieve explicit clip modeling, which is information-redundant and requires a large storage overhead.
Detect Everything with Few Examples
DE-ViT establishes new state-of-the-art results on all benchmarks.
Ranked #1 on
Few-Shot Object Detection
on MS-COCO (30-shot)
ALWOD: Active Learning for Weakly-Supervised Object Detection
In this work, we propose ALWOD, a new framework that addresses this problem by fusing active learning (AL) with weakly and semi-supervised object detection paradigms.
MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation
We propose MISSRec, a multi-modal pre-training and transfer learning framework for SR. On the user side, we design a Transformer-based encoder-decoder model, where the contextual encoder learns to capture the sequence-level multi-modal user interests while a novel interest-aware decoder is developed to grasp item-modality-interest relations for better sequence representation.
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping
Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments.
Graph-based Topology Reasoning for Driving Scenes
Understanding the road genome is essential to realize autonomous driving.
Ranked #5 on
3D Lane Detection
on OpenLane-V2 val
D2DF2WOD: Learning Object Proposals for Weakly-Supervised Object Detection via Progressive Domain Adaptation
In its warm-up domain adaptation stage, the model learns a fully-supervised object detector (FSOD) to improve the precision of the object proposals in the target domain, and at the same time learns target-domain-specific and detection-aware proposal features.
Contrastive Masked Autoencoders for Self-Supervised Video Hashing
To capture video semantic information for better hashing learning, we adopt an encoder-decoder structure to reconstruct the video from its temporal-masked frames.
TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction
This technical report presents an effective method for motion prediction in autonomous driving.
Ranked #12 on
Motion Forecasting
on Argoverse CVPR 2020
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic correlation function between redshifts 0.6 and 1
We present the cosmological analysis of the configuration-space anisotropic clustering in the completed Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 galaxy sample.
Cosmology and Nongalactic Astrophysics
The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: a multi-tracer analysis in Fourier space for measuring the cosmic structure growth and expansion rate
We perform a joint BAO and RSD analysis using the eBOSS DR16 LRG and ELG samples in the redshift range of $z\in[0. 6, 1. 1]$, and detect a RSD signal from the cross power spectrum at a $\sim4\sigma$ confidence level, i. e., $f\sigma_8=0. 317\pm0. 080$ at $z_{\rm eff}=0. 77$.
Cosmology and Nongalactic Astrophysics
The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR16 luminous red galaxy and emission line galaxy samples: cosmic distance and structure growth measurements using multiple tracers in configuration space
We perform a multi-tracer analysis using the complete Sloan Digital Sky Survey IV (SDSS-IV) extended Baryon Oscillation Spectroscopic Survey (eBOSS) DR16 luminous red galaxy (LRG) and the DR16 emission line galaxy (ELG) samples in the configuration space, and successfully detect a cross correlation between the two samples, and find the growth rate to be $f\sigma_8=0. 342 \pm 0. 085$ ($\sim25$ per cent accuracy) from the cross sample alone.
Cosmology and Nongalactic Astrophysics
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs
A number of cross-lingual transfer learning approaches based on neural networks have been proposed for the case when large amounts of parallel text are at our disposal.
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement
We propose a family of novel hierarchical Bayesian deep auto-encoder models capable of identifying disentangled factors of variability in data.
Relevance Factor VAE: Learning and Identifying Disentangled Factors
We propose a novel VAE-based deep auto-encoder model that can learn disentangled latent representations in a fully unsupervised manner, endowed with the ability to identify all meaningful sources of variation and their cardinality.
Generative Adversarial Talking Head: Bringing Portraits to Life with a Weakly Supervised Neural Network
This paper presents Generative Adversarial Talking Head (GATH), a novel deep generative neural network that enables fully automatic facial expression synthesis of an arbitrary portrait with continuous action unit (AU) coefficients.
End-to-end Learning for 3D Facial Animation from Raw Waveforms of Speech
We present a deep learning framework for real-time speech-driven 3D facial animation from just raw waveforms.
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: a tomographic analysis of structure growth and expansion rate from anisotropic galaxy clustering
In order to extract the redshift information of anisotropic galaxy clustering, we analyse this data set in nine overlapping redshift slices in configuration space and perform the joint constraints on the parameters $(D_V, F_{\mathrm{AP}}, f\sigma_8)$ using the correlation function multipoles.
Cosmology and Nongalactic Astrophysics
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: tomographic BAO analysis of DR12 combined sample in configuration space
Splitting the sample into multiple overlapping redshift slices to extract the redshift information of galaxy clustering, we obtain a measurement of $D_A(z)/r_d$ and $H(z)r_d$ at nine effective redshifts with the full covariance matrix calibrated using MultiDark-Patchy mock catalogues.
Cosmology and Nongalactic Astrophysics
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample
When combined with supernova Ia data, we find H0 = 67. 3+/-1. 0 km/s/Mpc even for our most general dark energy model, in tension with some direct measurements.
Cosmology and Nongalactic Astrophysics
