Finally, meet your #3DV2026 Publicity Chairs! 📢 @hanwenjiang1 @yanxg.bsky.social @chih-hao.bsky.social @csprofkgd.bsky.social We’ll keep the 3DV conversation alive: posting updates, refreshing the website, and listening to your feedback. Got questions or ideas? Tag @3dvconf.bsky.social anytime!

Introducing your #3DV2026 📝Publication Chairs &🔍Research Interaction Chairs! 📝Publication Chairs ensure accepted papers are properly published in the conference proceedings 🔍Research Interaction Chairs encourage engagement by spotlighting exceptional research in 3D vision

Understanding and reconstructing the 3D world are at the heart of computer vision and graphics. At #CVPR2025, we’ve seen many exciting works in 3D vision. If you're pushing the boundaries, please consider submitting your work to #3DV2026 in Vancouver! (Deadline: Aug. 18, 2025)

Excited to share our work at #CVPR2025! 👁️IRIS estimates accurate surface material, spatially-varying HDR lighting, and camera response function given a set of LDR images! It enables realistic, view-consistent, and controllable relighting and object insertion. (links in 🧵)

I’m thrilled to share that I will be joining Johns Hopkins University’s Department of Computer Science (@jhucompsci.bsky.social, @hopkinsdsai.bsky.social) as an Assistant Professor this fall.

📢 3DV 2026 – Call for Papers is Out! 📝 Paper Deadline: Aug 18 🎥 Supplementary: Aug 21 🔗 3dvconf.github.io/2026/call-fo... 📅 Conference Date: Mar 20–23, 2026 🌆 Location: Vancouver 🇨🇦 🚀 Showcase your latest research to the world! #3DV2026 #CallForPapers #Vancouver #Canada

🔊 New NVIDIA paper: Audio-SDS 🔊 We repurpose Score Distillation Sampling (SDS) for audio, turning any pretrained audio diffusion model into a tool for diverse tasks, including source separation, impact synthesis & more. 🎧 Demos, audio examples, paper: research.nvidia.com/labs/toronto... 🧵below

What if you could control the weather in any video — just like applying a filter? Meet WeatherWeaver, a video model for controllable synthesis and removal of diverse weather effects — such as 🌧️ rain, ☃️ snow, 🌁 fog, and ☁️ clouds — for any input video.

[1/10] Is scene understanding solved? Models today can label pixels and detect objects with high accuracy. But does that mean they truly understand scenes? Super excited to share our new paper and a new task in computer vision: Visual Jenga! 📄 arxiv.org/abs/2503.21770 🔗 visualjenga.github.io

🎬Imagine creating professional visual effects (VFX) with just words! We are excited to introduce AutoVFX, a framework that creates realistic video effects from natural language instructions! This is a cool project led by Hao-Yu, and we will present it at #3DV 2025!

Can we create realistic renderings of urban scenes from a single video while enabling controllable editing: relighting, object compositing, and nighttime simulation? Check out our #3DV2025 UrbanIR paper, led by @chih-hao.bsky.social that does exactly this. 🔗: urbaninverserendering.github.io

Check out UrbanIR - Inverse rendering of unbounded scenes from a single video! It’s a super cool project led by the amazing Chih-Hao! @chih-hao.bsky.social is a rising star in 3DV! Follow him! Learn more here👇

✨What if we could transform a daytime driving video into a realistic nighttime scene—without ever stepping outside again? We introduce UrbanIR, a neural rendering framework for 💡relighting, 🌃nighttime simulation, and 🚘 object insertion—all from a single video of urban scenes!

How do we go beyond colors and recover the intrinsic scene properties? 🤔 👁️ IRIS: Inverse Rendering of Indoor Scenes IRIS estimates accurate material, lighting, and camera response functions given a set of LDR images, enabling photorealistic and view-consistent relighting and object insertion.