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Found 23 papers, 17 papers with code
HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
The proposed Historical Prediction Attention together with the Agent Attention and Mode Attention is further formulated as the Triple Factorized Attention module, serving as the core design of HPNet. Experiments on the Argoverse and INTERACTION datasets show that HPNet achieves state-of-the-art performance, and generates accurate and stable future trajectories.
Black-Box Tuning of Vision-Language Models with Effective Gradient Approximation
Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios.
Decoupled Textual Embeddings for Customized Image Generation
To decouple irrelevant attributes (i. e., background and pose) from the subject embedding, we further present several attribute mappers that encode each image as several image-specific subject-unrelated embeddings.
Unveiling the Implicit Toxicity in Large Language Models
While recent studies primarily focus on probing toxic outputs that can be easily detected with existing toxicity classifiers, we show that LLMs can generate diverse implicit toxic outputs that are exceptionally difficult to detect via simply zero-shot prompting.
GPT Can Solve Mathematical Problems Without a Calculator
Previous studies have typically assumed that large language models are unable to accurately perform arithmetic operations, particularly multiplication of >8 digits, and operations involving decimals and fractions, without the use of calculator tools.
Patch Is Not All You Need
Vision Transformers have achieved great success in computer visions, delivering exceptional performance across various tasks.
LRANet: Towards Accurate and Efficient Scene Text Detection with Low-Rank Approximation Network
Next, we propose a dual assignment scheme for speed acceleration.
DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model
Multilingual self-supervised speech representation models have greatly enhanced the speech recognition performance for low-resource languages, and the compression of these huge models has also become a crucial prerequisite for their industrial application.
Inferring and Leveraging Parts from Object Shape for Improving Semantic Image Synthesis
Despite the progress in semantic image synthesis, it remains a challenging problem to generate photo-realistic parts from input semantic map.
TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognition
In this work, we introduce TPS++, an attention-enhanced TPS transformation that incorporates the attention mechanism to text rectification for the first time.
Ranked #1 on
Scene Text Recognition
on SVT-P
CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model
While the style aggregator module is to generate paintings of a style corresponding to a reference image.
Dual Contrastive Prediction for Incomplete Multi-view Representation Learning
In this article, we propose a unified framework to solve the following two challenging problems in incomplete multi-view representation learning: i) how to learn a consistent representation unifying different views, and ii) how to recover the missing views.
ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation
In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation.
1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation
The task of referring video object segmentation aims to segment the object in the frames of a given video to which the referring expressions refer.
Position-Aware Contrastive Alignment for Referring Image Segmentation
The main challenge of this task is to understand the visual and linguistic content simultaneously and to find the referred object accurately among all instances in the image.
Texts as Images in Prompt Tuning for Multi-Label Image Recognition
Nonetheless, visual data (e. g., images) is by default prerequisite for learning prompts in existing methods.
Contrastive Learning
Multi-label Image Recognition with Partial Labels
1st Place Solutions for UG2+ Challenge 2022 ATMOSPHERIC TURBULENCE MITIGATION
In this technical report, we briefly introduce the solution of our team ''summer'' for Atomospheric Turbulence Mitigation in UG$^2$+ Challenge in CVPR 2022.
1st Place Solutions for the UVO Challenge 2022
This paper describes the approach we have taken in the challenge.
Summary on the ISCSLP 2022 Chinese-English Code-Switching ASR Challenge
Code-switching automatic speech recognition becomes one of the most challenging and the most valuable scenarios of automatic speech recognition, due to the code-switching phenomenon between multilingual language and the frequent occurrence of code-switching phenomenon in daily life.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition
Recently, most handwritten mathematical expression recognition (HMER) methods adopt the encoder-decoder networks, which directly predict the markup sequences from formula images with the attention mechanism.
Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks
In this paper, we present a novel one-shot generative domain adaption method, i. e., DiFa, for diverse generation and faithful adaptation.
TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline
Using TALCS corpus, we conduct ASR experiments in two popular speech recognition toolkits to make a baseline system, including ESPnet and Wenet.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
BERT-LID: Leveraging BERT to Improve Spoken Language Identification
It has a profound impact on the multilingual interoperability of an intelligent speech system.
