activity
20232026
most citedReuse and Diffuse: Iterative Denoising for Text-to-Video Generation

9 citations · 19 across the 20 of their papers we have counts for

collaborators

20 papers

cs.CV2026

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

Weitong Cai, Hang Zhang, Yukai Huang +6

Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses temporal structure, while text…

cs.CV2026

Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing

Weitong Cai, Hang Zhang, Yukai Huang +5

Always-on sensing is essential for next-generation edge/wearable AI systems, yet continuous high-fidelity RGB video capture remains prohibitively expensive for resource-constrained…

cs.CL2026

Top 10 Open Challenges Steering the Future of Diffusion Language Model and Its Variants

Yunhe Wang, Kai Han, Huiling Zhen +13

The paradigm of Large Language Models (LLMs) is currently defined by auto-regressive (AR) architectures, which generate text through a sequential ``brick-by-brick'' process. Despit…

cs.CV2026

Map2Thought: Explicit 3D Spatial Reasoning via Metric Cognitive Maps

Xiangjun Gao, Zhensong Zhang, Dave Zhenyu Chen +4

We propose Map2Thought, a framework that enables explicit and interpretable spatial reasoning for 3D VLMs. The framework is grounded in two key components: Metric Cognitive Map (Me…

cs.CV2025★ 4 cited

LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training

Xiang An, Yin Xie, Kaicheng Yang +20

We present LLaVA-OneVision-1.5, a novel family of Large Multimodal Models (LMMs) that achieve state-of-the-art performance with significantly reduced computational and financial co…

cs.CV2025

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving

Kai Chen, Ruiyuan Gao, Lanqing Hong +11

In this paper, we present details of the 1st W-CODA workshop, held in conjunction with the ECCV 2024. W-CODA aims to explore next-generation solutions for autonomous driving corner…

cs.AI2025★ 2 cited

Deep Research Agents: A Systematic Examination And Roadmap

Yuxuan Huang, Yihang Chen, Haozheng Zhang +10

The rapid progress of Large Language Models (LLMs) has given rise to a new category of autonomous AI systems, referred to as Deep Research (DR) agents. These agents are designed to…

cs.CV2024

MagicEraser: Erasing Any Objects via Semantics-Aware Control

Fan Li, Zixiao Zhang, Yi Huang +4

The traditional image inpainting task aims to restore corrupted regions by referencing surrounding background and foreground. However, the object erasure task, which is in increasi…

cs.CV2024

JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation

Chenhan Jiang, Yihan Zeng, Tianyang Hu +4

Score Distillation Sampling (SDS) by well-trained 2D diffusion models has shown great promise in text-to-3D generation. However, this paradigm distills view-agnostic 2D image distr…

cs.CV2024

AutoTVG: A New Vision-language Pre-training Paradigm for Temporal Video Grounding

Xing Zhang, Jiaxi Gu, Haoyu Zhao +6

Temporal Video Grounding (TVG) aims to localize a moment from an untrimmed video given the language description. Since the annotation of TVG is labor-intensive, TVG under limited s…

cs.CV2024★ 1 cited

The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

Bin Ren, Yawei Li, Nancy Mehta +129

This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this cha…

eess.IV2024

Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution

Qingping Zheng, Ling Zheng, Yuanfan Guo +4

Artifact-free super-resolution (SR) aims to translate low-resolution images into their high-resolution counterparts with a strict integrity of the original content, eliminating any…

cs.CV2024

LayerDiff: Exploring Text-guided Multi-layered Composable Image Synthesis via Layer-Collaborative Diffusion Model

Runhui Huang, Kaixin Cai, Jianhua Han +6

Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provi…

cs.CV2023

PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion

Guansong Lu, Yuanfan Guo, Jianhua Han +7

Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However,…

cs.CV2023★ 1 cited

DreamControl: Control-Based Text-to-3D Generation with 3D Self-Prior

Tianyu Huang, Yihan Zeng, Zhilu Zhang +5

3D generation has raised great attention in recent years. With the success of text-to-image diffusion models, the 2D-lifting technique becomes a promising route to controllable 3D…

cs.CV2023

BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models

Fengyuan Shi, Jiaxi Gu, Hang Xu +3

Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthes…

cs.CV2023★ 1 cited

Learning Unorthogonalized Matrices for Rotation Estimation

Kerui Gu, Zhihao Li, Shiyong Liu +6

Estimating 3D rotations is a common procedure for 3D computer vision. The accuracy depends heavily on the rotation representation. One form of representation -- rotation matrices -…

cs.CV2023

Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models

Tianyi Lu, Xing Zhang, Jiaxi Gu +5

Latent Diffusion Models (LDMs) are renowned for their powerful capabilities in image and video synthesis. Yet, compared to text-to-image (T2I) editing, text-to-video (T2V) editing…

cs.CV2023★ 9 cited

Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation

Jiaxi Gu, Shicong Wang, Haoyu Zhao +7

Inspired by the remarkable success of Latent Diffusion Models (LDMs) for image synthesis, we study LDM for text-to-video generation, which is a formidable challenge due to the comp…

cs.CV2023★ 1 cited

TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields

Tianyu Huang, Yihan Zeng, Bowen Dong +4

Recent works learn 3D representation explicitly under text-3D guidance. However, limited text-3D data restricts the vocabulary scale and text control of generations. Generators may…