🔥Vanast: VTON w/ Human Animation🔥

👉SNU unveils a novel unified framework that generates garment-transferred human animation videos directly from a single human/garment images, and pose guidance clip. Repo announced💙

👉Review https://t.ly/c0t79
👉Paper arxiv.org/pdf/2604.04934
👉Project hyunsoocha.github.io/vanast/
👉Repo github.com/snuvclab/vanast

🔥BoxerNet: SOTA 2D->3D BBs🔥

👉Boxer by META: transformer-based network to lift 2D BB proposals into 3D, followed by multi-view fusion and geometric filtering to produce globally consistent de-duplicated 3DBBs in metric world space. Repo under A-NC 4.0 International💙

👉Review https://t.ly/mlmV1
👉Paper https://arxiv.org/pdf/2604.05212
👉Project facebookresearch.github.io/boxer/
👉Repo github.com/facebookresearch/boxer

Hinton our guest in Pavia (remotely) 💚😈

Would you see a clip about the interview?

Here the preview, tomorrow the full clip from official source :)

🪞1.1M Metric VTON Dataset🪞

👉Google's Fit-Inclusive Try-on: large-scale VTO dataset comprising over 1.13M try-on image triplets accompanied by precise body and garment measurements. Repo & dataset announced💙

👉Review https://t.ly/cs-pt
👉Paper arxiv.org/pdf/2604.08526
👉Project johannakarras.github.io/FIT/
👉Repo TBA

🐞6D Object Pose w/ Deformation🐞

👉DeSOPE by Xidian & #MagicLeap is a novel large-scale dataset for 6DoF deformed objects: 665K pose annotations produced via a semiautomatic pipeline. Repo & Dataset announced💙

👉Review https://t.ly/M5VgX
👉Paper https://arxiv.org/pdf/2604.06720
👉Project https://desope-6d.github.io/
👉Repo TBA

🔥SOTA 3D Detection in the wild🔥

👉WildDet3D is a novel unified geometry-aware architecture for 3D detection that natively accepts text, point, and box prompts and can incorporate auxiliary depth signals at inference time. New SOTA! Repo, models and iphone 💙

👉Review https://t.ly/8NxBN
👉Paper arxiv.org/pdf/2604.08626
👉Project allenai.github.io/WildDet3D/
👉Repo github.com/allenai/WildDet3D

🧴OmniShow Content Creation🧴

👉OmniShow is the novel SOTA in content creation with industry-grade performance. Impressive results, best with audio. Repo announced💙

👉Review https://t.ly/Pm-7U
👉Paper arxiv.org/pdf/2604.11804
👉Project correr-zhou.github.io/OmniShow/
👉Repo github.com/Correr-Zhou/OmniShow

🐓Interactive Objects from EgoVideo🐓

👉EgoFun3D by Simon Fraser University is a coordinated task, dataset and benchmark for modeling interactive 3D objects from egocentric videos. Repo (TBA), demo & dataset💙

👉Review https://t.ly/YhGN7
👉Paper arxiv.org/pdf/2604.11038
👉Project 3dlg-hcvc.github.io/EgoFun3D/
👉Repo github.com/3dlg-hcvc/EgoFun3D
👉Demo bc79fea884062374b3.gradio.live/

📱3D Human-Object Contact📱

👉Pi-HOC by CMU + NREC is a novel single-pass, instance-aware framework for dense 3D semantic contact prediction of all human-object pairs. Repo announced💙

👉Review https://t.ly/TAgG1
👉Paper https://arxiv.org/pdf/2604.12923
👉Project https://pi-hoc.github.io/
👉Repo https://github.com/SravanChittupalli/Pi-HOC

🐞GCT 3D Reconstruction🐞

👉ANT unveils LingBot-Map, a feed-forward 3D foundation model for reconstructing scenes from streaming data, built upon a geometric context transformer (GCT) architecture. Repo under A-NC 4.0 International💙

👉Review https://t.ly/ExodA
👉Paper https://arxiv.org/pdf/2604.14141
👉Project https://arxiv.org/pdf/2604.14141
👉Repo github.com/robbyant/lingbot-map

👩‍🦰Deformable 3D Hair👩‍🦰

👉Xi’an Jiaotong University unveils a novel method that reconstructs decoupled 3D Gaussian head avatars from a single input image: effortless hairstyle transfer with natural dynamic hair motion. Code announced💙

👉Review https://t.ly/kWZdd
👉Paper https://arxiv.org/pdf/2604.14782
👉Project yuansun-xjtu.github.io/CompHairHead.io/
👉Repo yuansun-xjtu.github.io/CompHairHead.io/

🌗Mobile Ultra-detailed Avatars🌗

👉Given skeletal poses and a virtual camera as inputs, MUA by Max Planck Institute produces photorealistic renderings and hyper-detailed geometry of animatable clothed humans. Repo announced💙

👉Review https://t.ly/QPCy6
👉Paper https://arxiv.org/pdf/2604.18583
👉Project https://vcai.mpi-inf.mpg.de/projects/MUA/
👉Repo TBA

🎈Face Anything 4D (SOTA)🎈

👉A novel unified 4D facial reconstruction and dense tracking from image sequences: new SOTA in facial single-image and mono-video depth estimation, dense 4D reconstruction, and 3D point tracking. Repo & Dataset announced💙

👉Review https://t.ly/zItie
👉Paper https://arxiv.org/pdf/2604.19702
👉Project kocasariumut.github.io/FaceAnything
👉Repo TBA

💙 PY4AI 2026: here we are! 💙

👉The third edition of our conference is official! Speaker list and (free) tickets: https://t.ly/L4_52

🛒 Reshoot-Anything is out 🛒

👉Reshoot-Anything reshoots dynamic monocular videos under novel camera trajectories. Code under Apache 2.0 💙

👉Review https://t.ly/MIqAc
👉Paper https://arxiv.org/pdf/2604.21776
👉Project adithyaiyer1999.github.io/reshoot-anything/
👉Repo github.com/morphicfilms/video-to-video

🧘‍♀️Holistic Shot Boundary Detection🧘‍♀️

👉OmniShotCut detects shot changes of the video in diverse sources (anime, vlog, game, shorts, sports, screen recording, etc.), and recognize Sudden Jump and Transitions (dissolve, fade, wipe, etc.) by proposing a Shot-Query-based Video Transformer. Repo, demo & benchmark💙

👉Review https://t.ly/sTi7N
👉Paper https://arxiv.org/pdf/2604.24762
👉Project uva-computer-vision-lab.github.io/OmniShotCut_website/
👉Repo github.com/UVA-Computer-Vision-Lab/OmniShotCut

🪝Syn4D: Multiview Synthetic 4D Dataset🪝

👉Syn4D is novel multi-view synthetic dataset of dynamic scenes that includes ground-truth camera motion, depth maps, dense tracking, and parametric human pose annotations💙

👉Review https://t.ly/SL1mk
👉Paper https://arxiv.org/pdf/2605.05207
👉Project https://jzr99.github.io/Syn4D/
👉Repo https://github.com/jzr99/Syn4D
👉Data huggingface.co/datasets/Syn4D/Syn4D_RGBD/tree/main

🦄Unified Correspondence Transformer🦄

👉UniCorrn is the first correspondence model with shared weights that unifies 2D-2D, 2D-3D, and 3D-3D geometric matching with a transformer. CC BY-NC-SA 4.0💙

👉Review https://t.ly/2OBdq
👉Paper https://arxiv.org/pdf/2605.04044
👉Project https://neu-vi.github.io/UniCorrn/
👉Repo https://github.com/neu-vi/UniCorrn