Search Results for author:
Found 16 papers, 5 papers with code
VideoGen-Eval: Agent-based System for Video Generation Evaluation
The rapid advancement of video generation has rendered existing evaluation systems inadequate for assessing state-of-the-art models, primarily due to simple prompts that cannot showcase the model's capabilities, fixed evaluation operators struggling with Out-of-Distribution (OOD) cases, and misalignment between computed metrics and human preferences.
BlobCtrl: A Unified and Flexible Framework for Element-level Image Generation and Editing
Element-level visual manipulation is essential in digital content creation, but current diffusion-based methods lack the precision and flexibility of traditional tools.
Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine
In this paper, we introduce a novel end-to-end multimodal large language model for the biomedical domain, named MedPLIB, which possesses pixel-level understanding.
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
Specifically, we generate a dense motion field from a sparse motion field and the reference image, which provides region-level dense guidance while maintaining the generalization of the sparse pose control.
Deep Learning Autoencoders for Reducing PAPR in Coherent Optical Systems
In particular, the AE model achieves the best BER performance of \(2 \times 10^{-6}\) at 44 dB OSNR, surpassing traditional methods.
Textual Inversion and Self-supervised Refinement for Radiology Report Generation
Existing mainstream approaches follow the encoder-decoder paradigm for generating radiology reports.
Towards Spoken Language Understanding via Multi-level Multi-grained Contrastive Learning
SLU usually consists of two subtasks, including intent detection and slot filling.
Uncertainty-aware sign language video retrieval with probability distribution modeling
Sign language video retrieval plays a key role in facilitating information access for the deaf community.
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation
Recent developments underscore the potential of textual information in enhancing learning models for a deeper understanding of medical visual semantics.
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction
Fine-grained few-shot entity extraction in the chemical domain faces two unique challenges.
ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding
Specifically, in fine-tuning, we apply mutual learning and train two SLU models on the manual transcripts and the ASR transcripts, respectively, aiming to iteratively share knowledge between these two models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
G2L: Semantically Aligned and Uniform Video Grounding via Geodesic and Game Theory
Due to two annoying issues in video grounding: (1) the co-existence of some visual entities in both ground truth and other moments, \ie semantic overlapping; (2) only a few moments in the video are annotated, \ie sparse annotation dilemma, vanilla contrastive learning is unable to model the correlations between temporally distant moments and learned inconsistent video representations.
Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generation
Automatic radiology report generation has attracted enormous research interest due to its practical value in reducing the workload of radiologists.
Exploiting Auxiliary Caption for Video Grounding
Video grounding aims to locate a moment of interest matching the given query sentence from an untrimmed video.
Macroblock Classification Method for Video Applications Involving Motions
We demonstrate that this low-computation-complexity method can efficiently catch the characteristics of the frame.
A new network-based algorithm for human activity recognition in video
Based on this network, we further model people in the scene as packages while human activities can be modeled as the process of package transmission in the network.
