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09/08/2023
Language Prompt for Autonomous Driving
A new trend in the computer vision community is to capture objects of in...
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07/18/2023
OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims at segmenting an object ...
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06/06/2023
Impact of Large Language Models on Generating Software Specifications
Software specifications are essential for ensuring the reliability of so...
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06/05/2023
LmPa: Improving Decompilation by Synergy of Large Language Model and Program Analysis
Decompilation aims to recover the source code form of a binary executabl...
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05/23/2023
MOTRv3: Release-Fetch Supervision for End-to-End Multi-Object Tracking
Although end-to-end multi-object trackers like MOTR enjoy the merits of ...
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04/28/2023
Fusion is Not Enough: Single-Modal Attacks to Compromise Fusion Models in Autonomous Driving
Multi-sensor fusion (MSF) is widely adopted for perception in autonomous...
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04/15/2023
Align-DETR: Improving DETR with Simple IoU-aware BCE loss
DETR has set up a simple end-to-end pipeline for object detection by for...
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03/23/2023
Detecting Backdoors in Pre-trained Encoders
Self-supervised learning in computer vision trains on unlabeled data, su...
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03/21/2023
Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
In this paper, we propose a long-sequence modeling framework, named Stre...
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03/20/2023
VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking
3D object detectors usually rely on hand-crafted proxies, e.g., anchors ...
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02/03/2023
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
Automated Program Repair (APR) improves software reliability by generati...
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12/22/2022
Reversible Column Networks
We propose a new neural network design paradigm Reversible Column Networ...
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11/21/2022
Twin-S: A Digital Twin for Skull-base Surgery
Purpose: Digital twins are virtual interactive models of the real world,...
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11/17/2022
MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors
In this paper, we propose MOTRv2, a simple yet effective pipeline to boo...
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10/27/2022
The 1st-place Solution for ECCV 2022 Multiple People Tracking in Group Dance Challenge
We present our 1st place solution to the Group Dance Multiple People Tra...
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06/21/2022
Scaling up Kernels in 3D CNNs
Recent advances in 2D CNNs and vision transformers (ViTs) reveal that la...
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06/02/2022
PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
In this paper, we propose PETRv2, a unified framework for 3D perception ...
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05/30/2022
Re-parameterizing Your Optimizers rather than Architectures
The well-designed structures in neural networks reflect the prior knowle...
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04/10/2022
Simple Baselines for Image Restoration
Although there have been significant advances in the field of image rest...
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03/15/2022
Progressive End-to-End Object Detection in Crowded Scenes
In this paper, we propose a new query-based detection framework for crow...
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12/19/2021
On Efficient Transformer and Image Pre-training for Low-level Vision
Pre-training has marked numerous state of the arts in high-level compute...
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10/25/2021
Instance-Conditional Knowledge Distillation for Object Detection
Despite the success of Knowledge Distillation (KD) on image classificati...
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06/30/2021
The Threat of Offensive AI to Organizations
AI has provided us with the ability to automate tasks, extract informati...
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01/11/2021
RepVGG: Making VGG-style ConvNets Great Again
We present a simple but powerful architecture of convolutional neural ne...
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12/25/2020
Implicit Feature Pyramid Network for Object Detection
In this paper, we present an implicit feature pyramid network (i-FPN) fo...
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07/04/2020
Weight-dependent Gates for Network Pruning
In this paper, we propose a simple and effective network pruning framewo...
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05/18/2020
Joint Multi-Dimension Pruning
We present joint multi-dimension pruning (named as JointPruning), a new ...
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04/26/2020
Stitcher: Feedback-driven Data Provider for Object Detection
Object detectors commonly vary quality according to scales, where the pe...
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03/31/2019
Single Path One-Shot Neural Architecture Search with Uniform Sampling
One-shot method is a powerful Neural Architecture Search (NAS) framework...
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03/26/2019
DetNAS: Neural Architecture Search on Object Detection
Object detectors are usually equipped with networks designed for image c...
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09/23/2018
Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection
Non-maximum suppression (NMS) is essential for state-of-the-art object d...
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04/30/2018
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Human detection has witnessed impressive progress in recent years. Howev...
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11/20/2017
MegDet: A Large Mini-Batch Object Detector
The improvements in recent CNN-based object detection works, from R-CNN ...
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07/19/2017
Channel Pruning for Accelerating Very Deep Neural Networks
In this paper, we introduce a new channel pruning method to accelerate v...
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03/16/2016
Identity Mappings in Deep Residual Networks
Deep residual networks have emerged as a family of extremely deep archit...
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12/10/2015
Deep Residual Learning for Image Recognition
Deeper neural networks are more difficult to train. We present a residua...
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06/18/2014
